Geological Inference from Textual Data using Word Embeddings


GeomCA: Geometric Evaluation of Data Representations


GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules


GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction


Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation


Geometric Adversarial Attacks and Defenses on 3D Point Clouds


Geometric All-Way Boolean Tensor Decomposition


Geometric Approaches to Matrix Normalization and Graph Balancing


Geometric Deep Learning for Autonomous Driving: Unlocking the Power of Graph Neural Networks With CommonRoad-Geometric


Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface


Geometric Deep Learning for Realized Covariance Matrix Forecasting


Geometric Deep Learning for Structure-Based Drug Design: A Survey


Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling


Geometric Design of Micro Scale Volumetric Receiver Using System-Level Inputs: An Application of Surrogate-Based Approach


Geometric Features Enhanced Human-Object Interaction Detection


Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos


Geometric Formulation of Unified Force-Impedance Control on SE(3) for Robotic Manipulators


Geometric Graph Learning with Extended Atom-Types Features for Protein-Ligand Binding Affinity Prediction


Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture


Geometric Insights into Support Vector Machine Behavior using the KKT Conditions


Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks


Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning


Geometric Localization of Waves on Thin Elastic Structures


Geometric MCMC for Infinite-Dimensional Inverse Problems


Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks


Geometric Matrix Completion: A Functional View


Geometric Mechanics of Contact-Switching Systems


Geometric Multimodal Contrastive Representation Learning


Geometric Neural Network based on Phase Space for BCI-EEG decoding


Geometric Perception based Efficient Text Recognition


Geometric Representation Condition Improves Equivariant Molecule Generation


Geometric Slosh-Free Tracking for Robotic Manipulators


Geometric Structure and Polynomial-time Algorithm of Game Equilibria


Geometric Total Variation for Image Vectorization, Zooming and Pixel Art Depixelizing


Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos


Geometric Transformer for End-to-End Molecule Properties Prediction


Geometric Transformers for Protein Interface Contact Prediction


Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training


Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates


Geometric approaches to assessing the numerical feasibility for conducting matching-adjusted indirect comparisons


Geometric averages of partitioned datasets


Geometric calibration of Colour and Stereo Surface Imaging System of ESA's Trace Gas Orbiter


Geometric compression of invariant manifolds in neural nets


Geometric constraints in protein folding


Geometric correspondence of noisy quantum dynamics and universal robust quantum gates


Geometric decomposition of abelian varieties of order 1


Geometric deep learning approach to knot theory


Geometric description of clustering in directed networks


Geometric ergodicity of Gibbs samplers for Bayesian error-in-variable regression


Geometric features for voxel-based surface recognition


Geometric frustration of hard-disk packings on cones


Geometric goodness of fit measure to detect patterns in data point clouds


Geometric graphs from data to aid classification tasks with graph convolutional networks


Geometric immunosuppression in CAR-T cell treatment: Insights from mathematical modeling


Geometric instability of graph neural networks on large graphs


Geometric integration of classical spin dynamics via a mean-field Schrödinger equation


Geometric interpretation of the general POE model for a serial-link robot via conversion into D-H parameterization


Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks


Geometric multigrid method for solving Poisson's equation on octree grids with irregular boundaries


Geometric numerical integration of Liénard systems via a contact Hamiltonian approach


Geometric planted matchings beyond the Gaussian model


Geometric properties of solutions to the total variation denoising problem


Geometric quantile-based measures of multivariate distributional characteristics


Geometric robustness of deep networks: analysis and improvement


Geometric sparsification in recurrent neural networks


Geometric-aware Pretraining for Vision-centric 3D Object Detection


GeometricImageNet: Extending convolutional neural networks to vector and tensor images


Geometrical Homogeneous Clustering for Image Data Reduction


Geometrical Stem Detection from Image Data for Precision Agriculture


Geometrical dynamics of edge-driven surface growth


Geometrically Convergent Simulation of the Extrema of Lévy Processes


Geometrically-driven Aggregation for Zero-shot 3D Point Cloud Understanding


Geometry Attention Transformer with Position-aware LSTMs for Image Captioning


Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary Domains


Geometry Constrained Weakly Supervised Object Localization


Geometry Contrastive Learning on Heterogeneous Graphs


Geometry Interaction Knowledge Graph Embeddings


Geometry Normalization Networks for Accurate Scene Text Detection


Geometry Reduced Order Modeling (GROM) with application to modeling of glymphatic function


Geometry Restoration and Dewarping of Camera-Captured Document Images


Geometry Score: A Method For Comparing Generative Adversarial Networks


Geometry Sharing Network for 3D Point Cloud Classification and Segmentation


Geometry Uncertainty Projection Network for Monocular 3D Object Detection


Geometry encoding for numerical simulations


Geometry meets semantics for semi-supervised monocular depth estimation


Geometry of Graph Partitions via Optimal Transport


Geometry of Lightning Self-Attention: Identifiability and Dimension


Geometry of Linear Neural Networks: Equivariance and Invariance under Permutation Groups


Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning


Geometry of ecological coexistence and niche differentiation


Geometry of orofacial neuromuscular signals: speech articulation decoding using surface electromyography


Geometry of quadratic maps via convex relaxation


Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances


Geometry of the Space of Partitioned Networks: A Unified Theoretical and Computational Framework


Geometry of the Visual Cortex with Applications to Image Inpainting and Enhancement


Geometry of the mirror models dual to the complete intersection of two cubics


Geometry of vectorial martingale optimal transport and robust option pricing


Geometry parameter estimation for sparse X-ray log imaging


Geometry vs growth: Internal consistency of the flat ΛCDM model with KiDS-1000


Geometry-Aware Gradient Algorithms for Neural Architecture Search


Geometry-Aware Instance Segmentation with Disparity Maps


Geometry-Aware Instrumental Variable Regression


Geometry-Aware Learning of Maps for Camera Localization


Geometry-Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances


Geometry-Aware Supertagging with Heterogeneous Dynamic Convolutions


Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation


Geometry-Based Layout Generation with Hyper-Relations AMONG Objects


Geometry-Based Region Proposals for Real-Time Robot Detection of Tabletop Objects


Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields


Geometry-Contrastive Transformer for Generalized 3D Pose Transfer


Geometry-Corrected Geodesic Motion Modeling with Per-Frame Camera Motion for 360-Degree Video Compression


Geometry-Free View Synthesis: Transformers and no 3D Priors


Geometry-Guided Street-View Panorama Synthesis from Satellite Imagery


Geometry-Informed Neural Operator Transformer


Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels


Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects


Geometry-aware Reconstruction and Fusion-refined Rendering for Generalizable Neural Radiance Fields


Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials


Geometry-aware neural solver for fast Bayesian calibration of brain tumor models


Geometry-based Distance Decomposition for Monocular 3D Object Detection


Geometry-based approximation of waves in complex domains


Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices


Geometry-enhanced Pre-training on Interatomic Potentials


Geometry-enhanced graph neural network for learning the smoothness of glassy dynamics from static structure


Geospatial Disparities: A Case Study on Real Estate Prices in Paris


Geospatial Mechanistic Interpretability of Large Language Models


Geospatial Perspective Reprojections for Ground-Based Sky Imaging System


Geospatial analysis of toponyms in geotagged social media posts


Geospatial distributions reflect rates of evolution of features of language


Geostatistical Learning: Challenges and Opportunities


Geostatistics for large datasets on Riemannian manifolds: a matrix-free approach


German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data


German also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset


German in Flux: Detecting Metaphoric Change via Word Entropy


Germany's current COVID-19 crisis is mainly driven by the unvaccinated


Gerrymandering and Compactness: Implementation Flexibility and Abuse


GestFormer: Multiscale Wavelet Pooling Transformer Network for Dynamic Hand Gesture Recognition


GestSync: Determining who is speaking without a talking head


Gestalt-Guided Image Understanding for Few-Shot Learning


Gesticulator: A framework for semantically-aware speech-driven gesture generation


Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time Warping


Gesture-aware Interactive Machine Teaching with In-situ Object Annotations


Gesture-to-Gesture Translation in the Wild via Category-Independent Conditional Maps


GestureGPT: Toward Zero-Shot Free-Form Hand Gesture Understanding with Large Language Model Agents


Get 'em Moles! : Learning Spelling and Pronunciation through an Educational Game


Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach


Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference


Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models


Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest Monitoring


Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing


Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence


Get an A in Math: Progressive Rectification Prompting


Get my drift? Catching LLM Task Drift with Activation Deltas


Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning


Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation


Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach


Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment


Getting More from Less: Large Language Models are Good Spontaneous Multilingual Learners


Getting More out of Large Language Models for Proofs


Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Models


Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning


Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models


Getting To Know You: User Attribute Extraction from Dialogues


Getting into the Flow: Towards Better Type Error Messages for Constraint-Based Type Inference


Getting it Right: Improving Spatial Consistency in Text-to-Image Models


Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints


Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models


Getting the most out of your tokenizer for pre-training and domain adaptation


Getting to Know Low-light Images with The Exclusively Dark Dataset


Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration


Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming


Getting to the Root of the Problem: Sums of Squares for Infinite Trees


Ghera: A Repository of Android App Vulnerability Benchmarks


Ghmerti at SemEval-2019 Task 6: A Deep Word- and Character-based Approach to Offensive Language Identification


Ghost Noise for Regularizing Deep Neural Networks


Ghost cycles exhibit increased entrainment and richer dynamics in response to external forcing compared to slow-fast systems


Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory


Ghost-free High Dynamic Range Imaging via Hybrid CNN-Transformer and Structure Tensor


GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems


GhostMinion: A Strictness-Ordered Cache System for Spectre Mitigation


Ghostly interactions in (1+1) dimensional classical field theory


GiFT: Gibbs Fine-Tuning for Code Generation


GiGL: Large-Scale Graph Neural Networks at Snapchat


GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction


GiMeFive: Towards Interpretable Facial Emotion Classification


GiNaCDE: the high-performance F-expansion and First Integral Methods with C++ library for solving Nonlinear Differential Equations


Giant Impacts and Debris Disk Morphology


Giant Molecular Cloud Catalogues for PHANGS-ALMA: Methods and Initial Results


Giant non-linear susceptibility of hydrogenic donors in silicon and germanium


Giant piezoelectric effects of topological structures in stretched ferroelectric membranes


GiantHunter: Accurate detection of giant virus in metagenomic data using reinforcement-learning and Monte Carlo tree search


GiantMIDI-Piano: A large-scale MIDI dataset for classical piano music


Gibbs Flow for Approximate Transport with Applications to Bayesian Computation


Gibbs Phenomenon Suppression in PDE-Based Statistical Spatio-Temporal Models


Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions


Gibbs randomness-compression proposition: An efficient deep learning


Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution


GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration


Gibson Env: Real-World Perception for Embodied Agents


GiftBTE: An efficient deterministic solver for non-gray phonon Boltzmann transport equation


Giga-SSL: Self-Supervised Learning for Gigapixel Images


Giga-scale Kernel Matrix Vector Multiplication on GPU


Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion


GigaAM: Efficient Self-Supervised Learner for Speech Recognition


GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence


GigaSLAM: Large-Scale Monocular SLAM with Hierarchical Gaussian Splats


GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement


GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio


GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generation


Gigapixel Histopathological Image Analysis using Attention-based Neural Networks


Gigapixel Whole-Slide Images Classification using Locally Supervised Learning


Gigs with Guarantees: Achieving Fair Wage for Food Delivery Workers


Gillespie algorithms for stochastic multiagent dynamics in populations and network


GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing


Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching


Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository


GisPy: A Tool for Measuring Gist Inference Score in Text


GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks


GistVis: Automatic Generation of Word-scale Visualizations from Data-rich Documents


Gistable: Evaluating the Executability of Python Code Snippets on GitHub


Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models


GitBug-Java: A Reproducible Benchmark of Recent Java Bugs


GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More


GitChameleon: Unmasking the Version-Switching Capabilities of Code Generation Models


GitGoodBench: A Novel Benchmark For Evaluating Agentic Performance On Git


GitHub Copilot AI pair programmer: Asset or Liability?


GitHub Copilot: the perfect Code compLeeter?


GitHub Discussions: An Exploratory Study of Early Adoption


GitHub Repositories with Links to Academic Papers: Public Access, Traceability, and Evolution


GitHub Sponsors: Exploring a New Way to Contribute to Open Source


GitHub Stargazers | Building Graph- and Edge-level Prediction Algorithms for Developer Social Networks


GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors


GitQ- Towards Using Badges as Visual Cues for GitHub Projects


GitRank: A Framework to Rank GitHub Repositories


GitRanking: A Ranking of GitHub Topics for Software Classification using Active Sampling


GitTables: A Large-Scale Corpus of Relational Tables


Gitor: Scalable Code Clone Detection by Building Global Sample Graph


Give me Some Hard Questions: Synthetic Data Generation for Clinical QA


Give me a hint: Can LLMs take a hint to solve math problems?


Given Users Recommendations Based on Reviews on Yelp


Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?


Giving Feedback on Interactive Student Programs with Meta-Exploration


Giving Space to Your Message: Assistive Word Segmentation for the Electronic Typing of Digital Minorities


Giving Up Control: Neurons as Reinforcement Learning Agents


Giving a Hand to Diffusion Models: a Two-Stage Approach to Improving Conditional Human Image Generation


Giving each task what it needs -- leveraging structured sparsity for tailored multi-task learning


GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM


Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation


Glance and Focus: Memory Prompting for Multi-Event Video Question Answering


Glance and Gaze: A Collaborative Learning Framework for Single-channel Speech Enhancement


Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection


Glance-MCMT: A General MCMT Framework with Glance Initialization and Progressive Association


GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection


Glancing Future for Simultaneous Machine Translation


Glancing Transformer for Non-Autoregressive Neural Machine Translation


Glass Hardness: Predicting Composition and Load Effects via Symbolic Reasoning-Informed Machine Learning


Glass Segmentation with RGB-Thermal Image Pairs


GlassMessaging: Supporting Messaging Needs During Daily Activities Using OST-HMDs


GlassNet: a multitask deep neural network for predicting many glass properties


GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction


GlideNet: Global, Local and Intrinsic based Dense Embedding NETwork for Multi-category Attributes Prediction


Glider: Global and Local Instruction-Driven Expert Router


Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points


Glimpse-Attend-and-Explore: Self-Attention for Active Visual Exploration


Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection


Glimpse: Generalized Locality for Scalable and Robust CT


Glinthawk: A Two-Tiered Architecture for Offline LLM Inference


Glioblastoma Multiforme Prognosis: MRI Missing Modality Generation, Segmentation and Radiogenomic Survival Prediction


Glioblastoma Tumor Segmentation using an Ensemble of Vision Transformers


Glitch rises as a test for rapid superfluid coupling in neutron stars


GlitchMiner: Mining Glitch Tokens in Large Language Models via Gradient-based Discrete Optimization


GlitchProber: Advancing Effective Detection and Mitigation of Glitch Tokens in Large Language Models


Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models


Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology


GloBug: Using Global Data in Fault Localization


GloNets: Globally Connected Neural Networks


GloSoFarID: Global multispectral dataset for Solar Farm IDentification in satellite imagery


GloTSFormer: Global Video Text Spotting Transformer


GloVeInit at SemEval-2020 Task 1: Using GloVe Vector Initialization for Unsupervised Lexical Semantic Change Detection


GlobEnc: Quantifying Global Token Attribution by Incorporating the Whole Encoder Layer in Transformers


Global $k$-means$++$: an effective relaxation of the global $k$-means clustering algorithm


Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose Estimation


Global Concept Explanations for Graphs by Contrastive Learning


Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis


Global Constraints with Prompting for Zero-Shot Event Argument Classification


Global Context Enhanced Graph Neural Networks for Session-based Recommendation


Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks


Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection


Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners


Global Contrastive Batch Sampling via Optimization on Sample Permutations


Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation


Global Convergence Analysis of the Power Proximal Point and Augmented Lagrangian Method


Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets


Global Convergence of Iteratively Reweighted Least Squares for Robust Subspace Recovery


Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities


Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs


Global Counterfactual Explainer for Graph Neural Networks


Global Crop-Specific Fertilization Dataset from 1961-2019


Global Depths for Irregularly Observed Multivariate Functional Data


Global Dynamics of Ordinary Differential Equations: Wall Labelings, Conley Complexes, and Ramp Systems


Global Estimates of L-band Vegetation Optical Depth and Soil Permittivity over Snow-covered Boreal Forests and Permafrost using SMAP Satellite Data


Global Estimation of Building-Integrated Facade and Rooftop Photovoltaic Potential by Integrating 3D Building Footprint and Spatio-Temporal Datasets


Global Evaluation for Decision Tree Learning


Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors


Global Explanations of Neural Networks: Mapping the Landscape of Predictions


Global Features are All You Need for Image Retrieval and Reranking


Global Geolocated Realtime Data of Interfleet Urban Transit Bus Idling


Global Group Fairness in Federated Learning via Function Tracking


Global Guarantees for Blind Demodulation with Generative Priors


Global HRTF Interpolation via Learned Affine Transformation of Hyper-conditioned Features


Global Hash Tables Strike Back! An Analysis of Parallel GROUP BY Aggregation


Global Hierarchical Neural Networks using Hierarchical Softmax


Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning


Global Instance Tracking: Locating Target More Like Humans


Global Layers: Non-IID Tabular Federated Learning


Global Learnable Attention for Single Image Super-Resolution


Global Lepton Flavour Violating Constraints on New Physics


Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression


Global Message Ordering using Distributed Kafka Clusters


Global Minima by Penalized Full-dimensional Scaling


Global Models for Time Series Forecasting: A Simulation Study


Global Neural CCG Parsing with Optimality Guarantees


Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting


Global Occlusion-Aware Transformer for Robust Stereo Matching


Global Optimal Path-Based Clustering Algorithm


Global Optimization Algorithm through High-Resolution Sampling


Global Optimization for Cardinality-constrained Minimum Sum-of-Squares Clustering via Semidefinite Programming


Global Optimization via Optimal Decision Trees


Global Optimization with A Power-Transformed Objective and Gaussian Smoothing


Global Patterns of Extreme Temperature Teleconnections Using Climate Network Analysis


Global Performance Guarantees for Localized Model Predictive Control


Global Performance Guarantees for Neural Network Models of AC Power Flow


Global Point Cloud Registration Network for Large Transformations


Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs


Global Precipitation Nowcasting of Integrated Multi-satellitE Retrievals for GPM: A U-Net Convolutional LSTM Architecture


Global Predecessor Indexing: Avoiding Binary Search in Weighted Job Scheduling


Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks


Global Proxy-based Hard Mining for Visual Place Recognition


Global RTK Positioning in Graphical State Space


Global Reactions to the Cambridge Analytica Scandal: An Inter-Language Social Media Study


Global Reasoning over Database Structures for Text-to-SQL Parsing


Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems


Global Second-order Pooling Convolutional Networks


Global Semantic Description of Objects based on Prototype Theory


Global Semantic Descriptors for Zero-Shot Action Recognition


Global Sensing and Measurements Reuse for Image Compressed Sensing


Global Sensitivity Analysis of Plasma Instabilities via Active Subspaces


Global Short-Term Forecasting of Covid-19 Cases


Global Solutions to Nonconvex Problems by Evolution of Hamilton-Jacobi PDEs


Global Spectral Filter Memory Network for Video Object Segmentation


Global Stellarator Coil Optimization with Quadratic Constraints and Objectives


Global Stock Market Volatility Forecasting Incorporating Dynamic Graphs and All Trading Days


Global Structure Knowledge-Guided Relation Extraction Method for Visually-Rich Document


Global Structure-Aware Diffusion Process for Low-Light Image Enhancement


Global Tests for Smoothed Functions in Mean Field Variational Additive Models


Global Textual Relation Embedding for Relational Understanding


Global Texture Enhancement for Fake Face Detection in the Wild


Global Tracking via Ensemble of Local Trackers


Global Transition-based Non-projective Dependency Parsing


Global Transport for Fluid Reconstruction with Learned Self-Supervision


Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data


Global Voices, Local Biases: Socio-Cultural Prejudices across Languages


Global Voxel Transformer Networks for Augmented Microscopy


Global analyses of Higgs portal singlet dark matter models using GAMBIT


Global analysis of charm mixing parameters and determination of the CKM angle $γ$


Global analysis of regulatory network dynamics: equilibria and saddle-node bifurcations


Global and Local Alignment Networks for Unpaired Image-to-Image Translation


Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning


Global and Local Attention-Based Transformer for Hyperspectral Image Change Detection


Global and Local Contrastive Learning for Joint Representations from Cardiac MRI and ECG


Global and Local Features through Gaussian Mixture Models on Image Semantic Segmentation


Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition


Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data


Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions


Global and Local Prompts Cooperation via Optimal Transport for Federated Learning


Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogates


Global and optimal probes for the top-quark effective field theory at future lepton colliders


Global asymptotic stability of the active disassembly model of flagellar length control


Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles


Global climate modeling of Saturn's atmosphere. Part II: multi-annual high-resolution dynamical simulations


Global convergence of Negative Correlation Extreme Learning Machine


Global convergence of ResNets: From finite to infinite width using linear parameterization


Global convergence of a BFGS-type algorithm for nonconvex multiobjective optimization problems


Global disease monitoring and forecasting with Wikipedia


Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning


Global fits of axion-like particles to XENON1T and astrophysical data


Global health science leverages established collaboration network to fight COVID-19


Global hybrid multiconfiguration pair-density functional theory


Global mapping of structures and properties of crystal materials


Global minimization of polynomial integral functionals


Global misinformation spillovers in the online vaccination debate before and during COVID-19


Global network control from local information


Global random walk for one-dimensional one-phase Stefan-type moving-boundary problems: Simulation results


Global random walk solvers for reactive transport and biodegradation processes in heterogeneous porous media


Global sensitivity metrics from active subspaces


Global stability of perturbed chemostat systems


Global study of nuclear modifications on parton distribution functions


Global transformer overheating from geomagnetic storms


Global universal approximation of functional input maps on weighted spaces


Global versus Local: Evaluating AlexNet Architectures for Tropical Cyclone Intensity Estimation


Global weather map reveals persistent top-of-atmosphere features on the nearest brown dwarfs


Global weight optimization of frame structures under free-vibration eigenvalue constraints


Global-Local Attention for Emotion Recognition


Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds


Global-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection


Global-Local Processing in Convolutional Neural Networks


Global-Local Regularization Via Distributional Robustness


Global-Local Self-Distillation for Visual Representation Learning


Global-Local Similarity for Efficient Fine-Grained Image Recognition with Vision Transformers


Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration


Global-Local Transformer for Brain Age Estimation


Global-Local Tree Search in VLMs for 3D Indoor Scene Generation


Global-Locally Self-Attentive Dialogue State Tracker


Global-correlated 3D-decoupling Transformer for Clothed Avatar Reconstruction


Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model


Global-local Motion Transformer for Unsupervised Skeleton-based Action Learning


Global-to-Local Modeling for Video-based 3D Human Pose and Shape Estimation


Global-to-Local Neural Networks for Document-Level Relation Extraction


GlobalFlowNet: Video Stabilization using Deep Distilled Global Motion Estimates


GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification


GlobalMamba: Global Image Serialization for Vision Mamba


GlobalMatch: Registration of Forest Terrestrial Point Clouds by Global Matching of Relative Stem Positions


GlobalPointer: Large-Scale Plane Adjustment with Bi-Convex Relaxation


GlobalTomo: A global dataset for physics-ML seismic wavefield modeling and FWI


GlobalTrack: A Simple and Strong Baseline for Long-term Tracking


GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems


Globally Consistent Multi-People Tracking using Motion Patterns


Globally Consistent Normal Orientation for Point Clouds by Regularizing the Winding-Number Field


Globally Consistent RGB-D SLAM with 2D Gaussian Splatting


Globally Consistent Video Depth and Pose Estimation with Efficient Test-Time Training


Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses


Globally Convergent Type-I Anderson Acceleration for Non-Smooth Fixed-Point Iterations


Globally Convergent Variational Inference


Globally Correlation-Aware Hard Negative Generation


Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks


Globally Optimal Data-Association-Free Landmark-Based Localization Using Semidefinite Relaxations


Globally Optimal Event-Based Divergence Estimation for Ventral Landing


Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes


Globally Optimal Inverse Kinematics as a Quadratic Program


Globally Optimal Solution to Inverse Kinematics of 7DOF Serial Manipulator


Globally Solving Concave Quadratic Programs via Doubly Nonnegative Relaxation


Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D CT Images


Globally optimal and scalable $N$-way matching of astronomy catalogs


Globally optimal vertical direction estimation in Atlanta World


Globally solving Non-Convex Quadratic Programs via Linear Integer Programming techniques


Globally time-reversible fluid simulations with smoothed particle hydrodynamics


Globally-centered autocovariances in MCMC


GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News Summarization


Glocal Energy-based Learning for Few-Shot Open-Set Recognition


Glocal Explanations of Expected Goal Models in Soccer


GlocalCLIP: Object-agnostic Global-Local Prompt Learning for Zero-shot Anomaly Detection


GloptiNets: Scalable Non-Convex Optimization with Certificates


Gloss Attention for Gloss-free Sign Language Translation


Gloss-Free End-to-End Sign Language Translation


Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining


Gloss2Text: Sign Language Gloss translation using LLMs and Semantically Aware Label Smoothing


Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages


GlotScript: A Resource and Tool for Low Resource Writing System Identification


GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks


GlucoLens: Explainable Postprandial Blood Glucose Prediction from Diet and Physical Activity


GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation


Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification


Gluing curves of genus 1 and 2 along their 2-torsion


Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)


GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals


GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning


Glyph-aware Embedding of Chinese Characters


GlyphDraw2: Automatic Generation of Complex Glyph Posters with Diffusion Models and Large Language Models


GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation


GlyphNet: Homoglyph domains dataset and detection using attention-based Convolutional Neural Networks


GlyphPattern: An Abstract Pattern Recognition for Vision-Language Models


Gnowee: A Hybrid Metaheuristic Optimization Algorithm for Constrained, Black Box, Combinatorial Mixed-Integer Design


Go Back in Time: Generating Flashbacks in Stories with Event Temporal Prompts


Go Beyond Black-box Policies: Rethinking the Design of Learning Agent for Interpretable and Verifiable HVAC Control


Go Beyond Imagination: Maximizing Episodic Reachability with World Models


Go Forth and Prosper: Language Modeling with Ancient Textual History


Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks


Go Static: Contextualized Logging Statement Generation


Go Wide, Go Deep: Quantifying the Impact of Scientific Papers through Influence Dispersion Trees


Go beyond End-to-End Training: Boosting Greedy Local Learning with Context Supply


Go viral or go broadcast? Characterizing the virality and growth of cascades


GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions


GoHD: Gaze-oriented and Highly Disentangled Portrait Animation with Rhythmic Poses and Realistic Expression


GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis


GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo


GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state


GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning


GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing


GoTube: Scalable Stochastic Verification of Continuous-Depth Models


Goal Exploration Augmentation via Pre-trained Skills for Sparse-Reward Long-Horizon Goal-Conditioned Reinforcement Learning


Goal Recognition as Reinforcement Learning


Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds


Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning


Goal-Aware Identification and Rectification of Misinformation in Multi-Agent Systems


Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives


Goal-Conditioned Generators of Deep Policies


Goal-Conditioned Q-Learning as Knowledge Distillation


Goal-Conditioned Reinforcement Learning: Problems and Solutions


Goal-Driven Explainable Clustering via Language Descriptions


Goal-Driven Reasoning in DatalogMTL with Magic Sets


Goal-Guided Transformer-Enabled Reinforcement Learning for Efficient Autonomous Navigation


Goal-Oriented A-Posteriori Estimation of Model Error as an Aid to Parameter Estimation


Goal-Oriented Gaze Estimation for Zero-Shot Learning


Goal-Oriented Medium Access with Distributed Belief Processing


Goal-Oriented Prompt Attack and Safety Evaluation for LLMs


Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning


Goal-Reaching Policy Learning from Non-Expert Observations via Effective Subgoal Guidance


Goal-Reaching Trajectory Design Near Danger with Piecewise Affine Reach-avoid Computation


Goal-based portfolio selection with mental accounting


Goal-constrained Planning Domain Model Verification of Safety Properties


Goal-directed Planning and Goal Understanding by Active Inference: Evaluation Through Simulated and Physical Robot Experiments


Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction


GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction Following


Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Tasks


Gobra: Modular Specification and Verification of Go Programs (extended version)


Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving


Gohberg-Semencul Estimation of Toeplitz Structured Covariance Matrices and Their Inverses


Going Beyond Feature Similarity: Effective Dataset Distillation based on Class-Aware Conditional Mutual Information


Going Beyond H&E and Oncology: How Do Histopathology Foundation Models Perform for Multi-stain IHC and Immunology?


Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations


Going Beyond Nouns With Vision & Language Models Using Synthetic Data


Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems


Going Deeper into Permutation-Sensitive Graph Neural Networks


Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection


Going Extreme: Comparative Analysis of Hate Speech in Parler and Gab


Going From Molecules to Genomic Variations to Scientific Discovery: Intelligent Algorithms and Architectures for Intelligent Genome Analysis


Going Further: Flatness at the Rescue of Early Stopping for Adversarial Example Transferability


Going Grayscale: The Road to Understanding and Improving Unlearnable Examples


Going In Style: Audio Backdoors Through Stylistic Transformations


Going Retro: Astonishingly Simple Yet Effective Rule-based Prosody Modelling for Speech Synthesis Simulating Emotion Dimensions


Going beyond $S_8$: fast inference of the matter power spectrum from weak-lensing surveys


Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations


Going beyond accuracy: estimating homophily in social networks using predictions


Going faster to see further: GPU-accelerated value iteration and simulation for perishable inventory control using JAX


Going... going... wrong: a test of the level-k (and cognitive hierarchy) models of bidding behaviour


Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection


GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory


Golden Cudgel Network for Real-Time Semantic Segmentation


Golden Noise for Diffusion Models: A Learning Framework


Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Models


Golden ratio primal-dual algorithm with linesearch


Golden rhythms as a theoretical framework for cross-frequency organization


Goldfish: An Efficient Federated Unlearning Framework


Goldfish: Monolingual Language Models for 350 Languages


Goldfish: Peer selection using Matrix completion in unstructured P2P network


Golem: An algorithm for robust experiment and process optimization


GolfDB: A Video Database for Golf Swing Sequencing


GollumFit: An IceCube Open-Source Framework for Binned-Likelihood Neutrino Telescope Analyses


GomalizingFlow.jl: A Julia package for Flow-based sampling algorithm for lattice field theory


Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning Dynamics


Gondola: a Parametric Robot Infrastructure for Repeatable Mobile Experiments


Goniometers are a Powerful Acoustic Feature for Music Information Retrieval Tasks


GooAQ: Open Question Answering with Diverse Answer Types


Good Classification Measures and How to Find Them


Good Data, Large Data, or No Data? Comparing Three Approaches in Developing Research Aspect Classifiers for Biomedical Papers


Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER


Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency


Good Features to Correlate for Visual Tracking


Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM


Good Intentions, Risky Inventions: A Method for Assessing the Risks and Benefits of AI in Mobile and Wearable Uses


Good Intentions: Adaptive Parameter Management via Intent Signaling


Good Keypoints for the Two-View Geometry Estimation Problem


Good News, Everyone! Context driven entity-aware captioning for news images


Good Questions Help Zero-Shot Image Reasoning


Good Semi-supervised Learning that Requires a Bad GAN


Good Teachers Explain: Explanation-Enhanced Knowledge Distillation


Good Time to Ask: A Learning Framework for Asking for Help in Embodied Visual Navigation


Good Vibes! Towards Phone-to-User Authentication Through Wristwatch Vibrations


Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data


Good elliptic curves with a specified torsion subgroup


Good position braid representatives and transversal slices of unipotent orbits


Good practices for Bayesian Optimization of high dimensional structured spaces


Good practices for clinical data warehouse implementation: a case study in France


Good-looking but Lacking Faithfulness: Understanding Local Explanation Methods through Trend-based Testing


GoodPoint: unsupervised learning of keypoint detection and description


Goodness of Fit Metrics for Multi-class Predictor


Goodness of Fit for Bayesian Generative Models with Applications in Population Genetics


Goodness of Pronunciation Pipelines for OOV Problem


Goodness of fit by Neyman-Pearson testing


Goodness of fit of relational event models


Goodness-of-Fit Tests for Linear Non-Gaussian Structural Equation Models


Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes


Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)


Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An Overview


Google Research Football: A Novel Reinforcement Learning Environment


Gorgeous: Create Your Desired Character Facial Makeup from Any Ideas


Gossip and Attend: Context-Sensitive Graph Representation Learning


GothX: a generator of customizable, legitimate and malicious IoT network traffic


Gotham Dataset 2025: A Reproducible Large-Scale IoT Network Dataset for Intrusion Detection and Security Research


Gotham Testbed: a Reproducible IoT Testbed for Security Experiments and Dataset Generation


Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks


Gotta Catch 'em All: Aggregating CVSS Scores


Gotta Detect 'Em All: Fake Base Station and Multi-Step Attack Detection in Cellular Networks


Gotta Go Fast When Generating Data with Score-Based Models


Gotta Hear Them All: Sound Source Aware Vision to Audio Generation


Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation


Gottesman-Kitaev-Preskill codes: A lattice perspective


GovernR: Provenance and Confidentiality Guarantees In Research Data Repositories


Governance of Ledger-Anchored Decentralized Identifiers


Government spending and multi-category treatment effects:The modified conditional independence assumption


GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns


GrEmLIn: A Repository of Green Baseline Embeddings for 87 Low-Resource Languages Injected with Multilingual Graph Knowledge


GrGadget: an N-body TreePM relativistic code for cosmological simulations


GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models


GraCo: Granularity-Controllable Interactive Segmentation


GraCoRe: Benchmarking Graph Comprehension and Complex Reasoning in Large Language Models


GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes


GraFIT: A toolbox for fast and accurate frequency response identification in Gravitational Wave Detectors


GraFPrint: A GNN-Based Approach for Audio Identification


GraFormer: Graph Convolution Transformer for 3D Pose Estimation


GraKeL: A Graph Kernel Library in Python


GraLMatch: Matching Groups of Entities with Graphs and Language Models


GraMMaR: Ground-aware Motion Model for 3D Human Motion Reconstruction


GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters


GraNNite: Enabling High-Performance Execution of Graph Neural Networks on Resource-Constrained Neural Processing Units


GraPPI: A Retrieve-Divide-Solve GraphRAG Framework for Large-scale Protein-protein Interaction Exploration


GraSP: Simple yet Effective Graph Similarity Predictions


GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentation


GraSS: Scalable Influence Function with Sparse Gradient Compression


GraSSRep: Graph-Based Self-Supervised Learning for Repeat Detection in Metagenomic Assembly


GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search


GraVoS: Voxel Selection for 3D Point-Cloud Detection


Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference


GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision


Grace periods in comparative effectiveness studies of sustained treatments


Graceful task adaptation with a bi-hemispheric RL agent


Grad DFT: a software library for machine learning enhanced density functional theory


Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images


Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions


Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation


GradAug: A New Regularization Method for Deep Neural Networks


GradBias: Unveiling Word Influence on Bias in Text-to-Image Generative Models


GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting


GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting


GradMax: Growing Neural Networks using Gradient Information


GradNav: Accelerated Exploration of Potential Energy Surfaces with Gradient-Based Navigation


GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis


GradSign: Model Performance Inference with Theoretical Insights


GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity


GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient


GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks


Grade Like a Human: Rethinking Automated Assessment with Large Language Models


Grade Score: Quantifying LLM Performance in Option Selection


GradeADreamer: Enhanced Text-to-3D Generation Using Gaussian Splatting and Multi-View Diffusion


Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit


Gradformer: Graph Transformer with Exponential Decay


Gradient Adjusting Networks for Domain Inversion


Gradient Alignment Improves Test-Time Adaptation for Medical Image Segmentation


Gradient Alignment for Cross-Domain Face Anti-Spoofing


Gradient Ascent Post-training Enhances Language Model Generalization


Gradient Ascent Pulse Engineering with Feedback


Gradient Boosting Decision Trees on Medical Diagnosis over Tabular Data


Gradient Boosting Neural Networks: GrowNet


Gradient Boosting Reinforcement Learning


Gradient Boosting With Piece-Wise Linear Regression Trees


Gradient COBRA: A kernel-based consensual aggregation for regression


Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization


Gradient Compression and Correlation Driven Federated Learning for Wireless Traffic Prediction


Gradient Correlation Subspace Learning against Catastrophic Forgetting


Gradient Descent Maximizes the Margin of Homogeneous Neural Networks


Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization


Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization


Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation


Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix


Gradient Energy Matching for Distributed Asynchronous Gradient Descent


Gradient Equilibrium in Online Learning: Theory and Applications


Gradient Estimation with Constant Scaling for Hybrid Quantum Machine Learning


Gradient Estimation with Discrete Stein Operators


Gradient Estimation with Stochastic Softmax Tricks


Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians


Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding


Gradient Flows and Riemannian Structure in the Gromov-Wasserstein Geometry


Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design


Gradient Gating for Deep Multi-Rate Learning on Graphs


Gradient Guidance for Diffusion Models: An Optimization Perspective


Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction


Gradient Importance Learning for Incomplete Observations


Gradient Informed Proximal Policy Optimization


Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning


Gradient Inversion with Generative Image Prior


Gradient Knowledge Distillation for Pre-trained Language Models


Gradient Leakage Defense with Key-Lock Module for Federated Learning


Gradient Map-Assisted Head and Neck Tumor Segmentation: A Pre-RT to Mid-RT Approach in MRI-Guided Radiotherapy


Gradient Methods for Solving Stackelberg Games


Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization


Gradient Normalization for Generative Adversarial Networks


Gradient Projection Memory for Continual Learning


Gradient Projection Newton Pursuit for Sparsity Constrained Optimization


Gradient Remedy for Multi-Task Learning in End-to-End Noise-Robust Speech Recognition


Gradient Rewiring for Editable Graph Neural Network Training


Gradient Routing: Masking Gradients to Localize Computation in Neural Networks


Gradient Starvation: A Learning Proclivity in Neural Networks


Gradient Step Denoiser for convergent Plug-and-Play


Gradient Temporal-Difference Learning with Regularized Corrections


Gradient Tracking for High Dimensional Federated Optimization


Gradient Variance Loss for Structure-Enhanced Image Super-Resolution


Gradient Weight-normalized Low-rank Projection for Efficient LLM Training


Gradient and Newton Boosting for Classification and Regression


Gradient and Uncertainty Enhanced Sequential Sampling for Global Fit


Gradient based sample selection for online continual learning


Gradient boosting for convex cone predict and optimize problems


Gradient correlation is a key ingredient to accelerate SGD with momentum


Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth


Gradient descent with generalized Newton's method


Gradient elasticity in Swift-Hohenberg and phase-field crystal models


Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs


Gradient flows of interacting Laguerre cells as discrete porous media flows


Gradient penalty from a maximum margin perspective


Gradient representations in ReLU networks as similarity functions


Gradient scarcity with Bilevel Optimization for Graph Learning


Gradient weighting for speaker verification in extremely low Signal-to-Noise Ratio


Gradient-Annihilated PINNs for Solving Riemann Problems: Application to Relativistic Hydrodynamics


Gradient-Aware Logit Adjustment Loss for Long-tailed Classifier


Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual Claims


Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery


Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond


Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors


Gradient-Based Spectral Embeddings of Random Dot Product Graphs


Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction


Gradient-Boosted Generalized Linear Models for Conditional Vine Copulas


Gradient-Boosted Mixture Regression Models for Postprocessing Ensemble Weather Forecasts


Gradient-Driven 3D Segmentation and Affordance Transfer in Gaussian Splatting Using 2D Masks


Gradient-Free Adversarial Attacks for Bayesian Neural Networks


Gradient-Free Training of Recurrent Neural Networks using Random Perturbations


Gradient-Guided Annealing for Domain Generalization


Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models


Gradient-Guided Modality Decoupling for Missing-Modality Robustness


Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse Weather


Gradient-Leakage Resilient Federated Learning


Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI Segmentation


Gradient-Normalized Smoothness for Optimization with Approximate Hessians


Gradient-Weighted Feature Back-Projection: A Fast Alternative to Feature Distillation in 3D Gaussian Splatting


Gradient-based Adaptive Markov Chain Monte Carlo


Gradient-based Adversarial Attacks against Text Transformers


Gradient-based Automatic Mixed Precision Quantization for Neural Networks On-Chip


Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds


Gradient-based Editing of Memory Examples for Online Task-free Continual Learning


Gradient-based Hyperparameter Optimization Over Long Horizons


Gradient-based Hyperparameter Optimization through Reversible Learning


Gradient-based Intra-attention Pruning on Pre-trained Language Models


Gradient-based Jailbreak Images for Multimodal Fusion Models


Gradient-based Local Next-best-view Planning for Improved Perception of Targeted Plant Nodes


Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object Detection


Gradient-based Parameter Selection for Efficient Fine-Tuning


Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection


Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation


Gradient-based Uncertainty for Monocular Depth Estimation


Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus


Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective


Gradient-based deterministic inversion of geophysical data with Generative Adversarial Networks: is it feasible?


Gradient-based optimization for variational empirical Bayes multiple regression


Gradient-based optimization of 3D MHD equilibria


Gradient-based training of Gaussian Mixture Models for High-Dimensional Streaming Data


Gradient-descent methods for fast quantum state tomography


Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems


Gradient-enhanced sparse Hermite polynomial expansions for pricing and hedging high-dimensional American options


Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families


Gradient-free Multi-domain Optimization for Autonomous Systems


Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approach


Gradient-free algorithm for saddle point problems under overparametrization


Gradient-free training of neural ODEs for system identification and control using ensemble Kalman inversion


Gradient-free training of recurrent neural networks


Gradient-free variational learning with conditional mixture networks


Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD


Gradients Stand-in for Defending Deep Leakage in Federated Learning


Gradients and frequency profiles of quantum re-uploading models


Gradients of Functions of Large Matrices


Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild


Gradual (In)Compatibility of Fairness Criteria


Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks


Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent


Gradual Domain Adaptation via Normalizing Flows


Gradual Domain Adaptation without Indexed Intermediate Domains


Gradual Fine-Tuning for Low-Resource Domain Adaptation


Gradual Learning of Recurrent Neural Networks


Gradual Optimization Learning for Conformational Energy Minimization


Gradual Soundness: Lessons from Static Python


Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning


Gradual Weisfeiler-Leman: Slow and Steady Wins the Race


Gradualizing the Calculus of Inductive Constructions


Gradually Vanishing Bridge for Adversarial Domain Adaptation


Graduated Optimization of Black-Box Functions


Graffinity: Visualizing Connectivity In Large Graphs


Grafite: Taming Adversarial Queries with Optimal Range Filters


GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Feature


Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image Classification


Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization


GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure


GrainGrasp: Dexterous Grasp Generation with Fine-grained Contact Guidance


GrainSpace: A Large-scale Dataset for Fine-grained and Domain-adaptive Recognition of Cereal Grains


Gram Barcodes for Histopathology Tissue Texture Retrieval


Gram-Schmidt Methods for Unsupervised Feature Extraction and Selection


Gramformer: Learning Crowd Counting via Graph-Modulated Transformer


Gramian Multimodal Representation Learning and Alignment


Grammar Based Directed Testing of Machine Learning Systems


Grammar Control in Dialogue Response Generation for Language Learning Chatbots


Grammar Prompting for Domain-Specific Language Generation with Large Language Models


Grammar-Compressed Indexes with Logarithmic Search Time


Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning


Grammar-based Game Description Generation using Large Language Models


GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-Tuning


Grammatical Error Correction for Code-Switched Sentences by Learners of English


Grammatical Error Correction in Low-Resource Scenarios


Grammatical Profiling for Semantic Change Detection


Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddings


Grams: Gradient Descent with Adaptive Momentum Scaling


Grand canonically optimized grain boundary phases in hexagonal close-packed titanium


Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes


Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length


Granger causal inference on DAGs identifies genomic loci regulating transcription


Granger causality in the frequency domain: derivation and applications


Granger-causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks


Granite Code Models: A Family of Open Foundation Models for Code Intelligence


GrannGAN: Graph annotation generative adversarial networks


Grant-Free Random Access of IoT devices in Massive MIMO with Partial CSI


Grants4Companies: Applying Declarative Methods for Recommending and Reasoning About Business Grants in the Austrian Public Administration (System Description)


Granular Ball Twin Support Vector Machine


Granular Privacy Control for Geolocation with Vision Language Models


Granular clustering of de novo protein models


Granular conditional entropy-based attribute reduction for partially labeled data with proxy labels


Granularity at Scale: Estimating Neighborhood Socioeconomic Indicators from High-Resolution Orthographic Imagery and Hybrid Learning


Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering


Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure


Graph Algorithms for Multiparallel Word Alignment


Graph Analytics for Cyber-Physical System Resilience Quantification


Graph Anomaly Detection with Unsupervised GNNs


Graph Attention Network for Lane-Wise and Topology-Invariant Intersection Traffic Simulation


Graph Attention Transformer Network for Multi-Label Image Classification


Graph Attention for Automated Audio Captioning


Graph Attention for Heterogeneous Graphs with Positional Encoding


Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models


Graph Attention-Based Symmetry Constraint Extraction for Analog Circuits


Graph Attention-based Deep Reinforcement Learning for solving the Chinese Postman Problem with Load-dependent costs


Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction


Graph Auto-Encoders for Financial Clustering


Graph Backup: Data Efficient Backup Exploiting Markovian Transitions


Graph Based Network with Contextualized Representations of Turns in Dialogue


Graph Based Relational Features for Collective Classification


Graph Based Temporal Aggregation for Video Retrieval


Graph Bayesian Optimization for Multiplex Influence Maximization


Graph Bisection with Pareto-Optimization


Graph Bottlenecked Social Recommendation


Graph Capsule Convolutional Neural Networks


Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs


Graph Classification with GNNs: Optimisation, Representation and Inductive Bias


Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training


Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs


Graph Collaborative Signals Denoising and Augmentation for Recommendation


Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction


Graph Coloring with Physics-Inspired Graph Neural Networks


Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model


Graph Component Contrastive Learning for Concept Relatedness Estimation


Graph Compression Using The Regularity Method


Graph Conditional Flow Matching for Relational Data Generation


Graph Conditioned Sparse-Attention for Improved Source Code Understanding


Graph Consistency Based Mean-Teaching for Unsupervised Domain Adaptive Person Re-Identification


Graph Constrained Data Representation Learning for Human Motion Segmentation


Graph Constrained Reinforcement Learning for Natural Language Action Spaces


Graph Construction using Principal Axis Trees for Simple Graph Convolution


Graph Context Transformation Learning for Progressive Correspondence Pruning


Graph Contrastive Invariant Learning from the Causal Perspective


Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks


Graph Contrastive Learning for Anomaly Detection


Graph Contrastive Learning for Connectome Classification


Graph Contrastive Learning for Skeleton-based Action Recognition


Graph Contrastive Learning with Adaptive Augmentation


Graph Contrastive Learning with Augmentations


Graph Contrastive Learning with Cohesive Subgraph Awareness


Graph Contrastive Learning with Implicit Augmentations


Graph Convolution Machine for Context-aware Recommender System


Graph Convolution over Pruned Dependency Trees Improves Relation Extraction


Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments


Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection


Graph Convolutional Memory using Topological Priors


Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters


Graph Convolutional Network for Swahili News Classification


Graph Convolutional Network-based Feature Selection for High-dimensional and Low-sample Size Data


Graph Convolutional Networks Meet with High Dimensionality Reduction


Graph Convolutional Networks for Hyperspectral Image Classification


Graph Convolutional Networks for Temporal Action Localization


Graph Convolutional Networks for Traffic Forecasting with Missing Values


Graph Convolutional Networks for traffic anomaly


Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning


Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching


Graph Convolutional Neural Networks for analysis of EEG signals, BCI application


Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image


Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning


Graph Convolutions Enrich the Self-Attention in Transformers!


Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling


Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural Networks


Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning


Graph Cut-guided Maximal Coding Rate Reduction for Learning Image Embedding and Clustering


Graph Cuts with Arbitrary Size Constraints Through Optimal Transport


Graph Data Augmentation for Graph Machine Learning: A Survey


Graph Data Condensation via Self-expressive Graph Structure Reconstruction


Graph Denoising Diffusion for Inverse Protein Folding


Graph Denoising with Framelet Regularizer


Graph Diffusion Network for Drug-Gene Prediction


Graph Diffusion Transformers for Multi-Conditional Molecular Generation


Graph Distillation for Action Detection with Privileged Modalities


Graph Distillation with Eigenbasis Matching


Graph Domain Adaptation: Challenges, Progress and Prospects


Graph Dual-stream Convolutional Attention Fusion for Precipitation Nowcasting


Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials


Graph Edit Distance with General Costs Using Neural Set Divergence


Graph Embedded Intuitionistic Fuzzy Random Vector Functional Link Neural Network for Class Imbalance Learning


Graph Embedded Pose Clustering for Anomaly Detection


Graph Embedding Augmented Skill Rating System


Graph Embedding based Wireless Link Scheduling with Few Training Samples


Graph Embeddings via Tensor Products and Approximately Orthonormal Codes


Graph Enhanced Contrastive Learning for Radiology Findings Summarization


Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks


Graph Entropy Minimization for Semi-supervised Node Classification


Graph External Attention Enhanced Transformer


Graph Fairing Convolutional Networks for Anomaly Detection


Graph Federated Learning for CIoT Devices in Smart Home Applications


Graph Few-shot Class-incremental Learning


Graph Few-shot Learning via Knowledge Transfer


Graph Few-shot Learning with Task-specific Structures


Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation


Graph Foundation Models: A Comprehensive Survey


Graph Fourier Transformer with Structure-Frequency Information


Graph GOSPA metric: a metric to measure the discrepancy between graphs of different sizes


Graph Gamma Process Generalized Linear Dynamical Systems


Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics


Graph Generative Model for Benchmarking Graph Neural Networks


Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs


Graph Image Prior for Unsupervised Dynamic Cardiac Cine MRI Reconstruction


Graph Inductive Biases in Transformers without Message Passing


Graph Information Bottleneck for Subgraph Recognition


Graph Integration for Diffusion-Based Manifold Alignment


Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization


Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid


Graph Jigsaw Learning for Cartoon Face Recognition


Graph Kernels: State-of-the-Art and Future Challenges


Graph Laplacian for Image Anomaly Detection


Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks


Graph Learning Network: A Structure Learning Algorithm


Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs


Graph Learning based Recommender Systems: A Review


Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs


Graph Mamba: Towards Learning on Graphs with State Space Models


Graph Masked Autoencoders with Transformers


Graph Matching via convex relaxation to the simplex


Graph Matching with Bi-level Noisy Correspondence


Graph Meets LLMs: Towards Large Graph Models


Graph Meta Network for Multi-Behavior Recommendation


Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand


Graph Modeling in Computer Assisted Automotive Development


Graph Nets for Partial Charge Prediction


Graph Neural Controlled Differential Equations For Collaborative Filtering


Graph Neural Convection-Diffusion with Heterophily


Graph Neural Diffusion Networks for Semi-supervised Learning


Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series


Graph Neural Machine: A New Model for Learning with Tabular Data


Graph Neural Network Approach to Semantic Type Detection in Tables


Graph Neural Network Causal Explanation via Neural Causal Models


Graph Neural Network Encoding for Community Detection in Attribute Networks


Graph Neural Network Explanations are Fragile


Graph Neural Network Guided Local Search for the Traveling Salesperson Problem


Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems


Graph Neural Network contextual embedding for Deep Learning on Tabular Data


Graph Neural Network for Cell Tracking in Microscopy Videos


Graph Neural Network for Large-Scale Network Localization


Graph Neural Network for Predicting the Effective Properties of Polycrystalline Materials: A Comprehensive Analysis


Graph Neural Network for Traffic Forecasting: A Survey


Graph Neural Network to Dilute Outliers for Refactoring Monolith Application


Graph Neural Network with Local Frame for Molecular Potential Energy Surface


Graph Neural Network-Based Anomaly Detection for River Network Systems


Graph Neural Network-Based Anomaly Detection in Multivariate Time Series


Graph Neural Network-Based Pipeline for Track Finding in the Velo at LHCb


Graph Neural Network-Based Track Finding in the LHCb Vertex Detector


Graph Neural Network-Enhanced Expectation Propagation Algorithm for MIMO Turbo Receivers


Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning


Graph Neural Network-based Multi-agent Reinforcement Learning for Resilient Distributed Coordination of Multi-Robot Systems


Graph Neural Network-based Resource Allocation Strategies for Multi-Object Spectroscopy


Graph Neural Networks Accelerated Molecular Dynamics


Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective


Graph Neural Networks Exponentially Lose Expressive Power for Node Classification


Graph Neural Networks Inspired by Classical Iterative Algorithms


Graph Neural Networks Need Cluster-Normalize-Activate Modules


Graph Neural Networks Use Graphs When They Shouldn't


Graph Neural Networks and 3-Dimensional Topology


Graph Neural Networks and Applied Linear Algebra


Graph Neural Networks and Deep Reinforcement Learning Based Resource Allocation for V2X Communications


Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments


Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents


Graph Neural Networks based Log Anomaly Detection and Explanation


Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure


Graph Neural Networks embedded into Margules model for vapor-liquid equilibria prediction


Graph Neural Networks for Automatic Addition of Optimizing Components in Printed Circuit Board Schematics


Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites


Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities


Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection


Graph Neural Networks for Distributed Power Allocation in Wireless Networks: Aggregation Over-the-Air


Graph Neural Networks for Efficient AC Power Flow Prediction in Power Grids


Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes


Graph Neural Networks for Heart Failure Prediction on an EHR-Based Patient Similarity Graph


Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases


Graph Neural Networks for Learning Equivariant Representations of Neural Networks


Graph Neural Networks for Link Prediction with Subgraph Sketching


Graph Neural Networks for Multivariate Time Series Regression with Application to Seismic Data


Graph Neural Networks for Natural Language Processing: A Survey


Graph Neural Networks for Pressure Estimation in Water Distribution Systems


Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine


Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation


Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis


Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical Analysis


Graph Neural Networks for Surfactant Multi-Property Prediction


Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions


Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation


Graph Neural Networks for Wireless Communications: From Theory to Practice


Graph Neural Networks for an Accurate and Interpretable Prediction of the Properties of Polycrystalline Materials


Graph Neural Networks for modelling breast biomechanical compression


Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem


Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions


Graph Neural Networks in Computer Vision -- Architectures, Datasets and Common Approaches


Graph Neural Networks in Network Neuroscience


Graph Neural Networks in Recommender Systems: A Survey


Graph Neural Networks in TensorFlow and Keras with Spektral


Graph Neural Networks on Discriminative Graphs of Words


Graph Neural Networks with Adaptive Readouts


Graph Neural Networks with Diverse Spectral Filtering


Graph Neural Networks with Dynamic and Static Representations for Social Recommendation


Graph Neural Networks with Learnable Structural and Positional Representations


Graph Neural Networks with Learnable and Optimal Polynomial Bases


Graph Neural Networks with Local Graph Parameters


Graph Neural Networks with Parallel Neighborhood Aggregations for Graph Classification


Graph Neural Networks-Based User Pairing in Wireless Communication Systems


Graph Neural Networks-based Hybrid Framework For Predicting Particle Crushing Strength


Graph Neural Networks: A Review of Methods and Applications


Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification?


Graph Neural Ordinary Differential Equations


Graph Neural PDE Solvers with Conservation and Similarity-Equivariance


Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems


Graph Neural Processes for Spatio-Temporal Extrapolation


Graph Neural Prompting with Large Language Models


Graph Neural Rough Differential Equations for Traffic Forecasting


Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels


Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks


Graph Optimal Transport for Cross-Domain Alignment


Graph Out-of-Distribution Generalization via Causal Intervention


Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks


Graph Partitioning into Hamiltonian Subgraphs on a Quantum Annealer


Graph Pattern Mining and Learning through User-defined Relations (Extended Version)


Graph Perceiver IO: A General Architecture for Graph Structured Data


Graph Policy Gradients for Large Scale Robot Control


Graph Policy Network for Transferable Active Learning on Graphs


Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities


Graph Pooling via Coarsened Graph Infomax


Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification


Graph Prompt Learning: A Comprehensive Survey and Beyond


Graph Propagation Transformer for Graph Representation Learning


Graph Pseudometrics from a Topological Point of View


Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph


Graph Random Neural Features for Distance-Preserving Graph Representations


Graph Rationalization with Environment-based Augmentations


Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks


Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges


Graph Reinforcement Learning for Network Control via Bi-Level Optimization


Graph Representation Learning Beyond Node and Homophily


Graph Representation Learning Network via Adaptive Sampling


Graph Representation Learning for Contention and Interference Management in Wireless Networks


Graph Representation Learning for Parameter Transferability in Quantum Approximate Optimization Algorithm


Graph Representation Learning for Road Type Classification


Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation


Graph Representation-based Model Poisoning on Federated LLMs in CyberEdge Networks


Graph Representational Learning: When Does More Expressivity Hurt Generalization?


Graph Residual Noise Learner Network for Brain Connectivity Graph Prediction


Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning


Graph Sampling-based Meta-Learning for Molecular Property Prediction


Graph Self-Supervised Learning for Endoscopic Image Matching


Graph Self-Supervised Learning with Learnable Structural and Positional Encodings


Graph Self-supervised Learning with Accurate Discrepancy Learning


Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs


Graph Signal Processing for Cross-Domain Recommendation


Graph Signal Processing for Global Stock Market Realized Volatility Forecasting


Graph Signal Recovery Using Restricted Boltzmann Machines


Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution


Graph Sparsification via Mixture of Graphs


Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search


Graph Spectral Filtering with Chebyshev Interpolation for Recommendation


Graph Structural Attack by Perturbing Spectral Distance


Graph Structure Learning for Robust Graph Neural Networks


Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales


Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data


Graph Structure Learning with Variational Information Bottleneck


Graph Structure from Point Clouds: Geometric Attention is All You Need


Graph Structured Network for Image-Text Matching


Graph Structured Prediction Energy Networks


Graph Style Transfer for Counterfactual Explainability


Graph Summarization via Node Grouping: A Spectral Algorithm


Graph Summarization with Graph Neural Networks


Graph Theoretical Analysis of local ultraluminous infrared galaxies and quasars


Graph Topic Modeling for Documents with Spatial or Covariate Dependencies


Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution


Graph Transformation for Enzymatic Mechanisms


Graph Transformer for Graph-to-Sequence Learning


Graph Transformer with Disease Subgraph Positional Encoding for Improved Comorbidity Prediction


Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning


Graph Trend Filtering Networks for Recommendations


Graph Triple Attention Network: A Decoupled Perspective


Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models


Graph Wavelets via Sparse Cuts: Extended Version


Graph algorithms for predicting subcellular localization at the pathway level


Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Driving


Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos


Graph and distributed extensions of the Douglas-Rachford method


Graph as a feature: improving node classification with non-neural graph-aware logistic regression


Graph convolutional network for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution


Graph convolutional networks for learning with few clean and many noisy labels


Graph convolutions that can finally model local structure


Graph identification of proteins in tomograms (GRIP-Tomo)


Graph machine learning for flight delay prediction due to holding manouver


Graph neural network-based surrogate modelling for real-time hydraulic prediction of urban drainage networks


Graph neural networks and attention-based CNN-LSTM for protein classification


Graph neural networks and non-commuting operators


Graph neural networks informed locally by thermodynamics


Graph neural networks with configuration cross-attention for tensor compilers


Graph of Attacks: Improved Black-Box and Interpretable Jailbreaks for LLMs


Graph of Graphs: From Nodes to Supernodes in Graphical Models


Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs


Graph of Thoughts: Solving Elaborate Problems with Large Language Models


Graph representation forecasting of patient's medical conditions: towards a digital twin


Graph sketching-based Space-efficient Data Clustering


Graph sub-sampling for divide-and-conquer algorithms in large networks


Graph theory approach to exceptional points in wave scattering


Graph topological transformations in space-filling cell aggregates


Graph topology determines coexistence in the rock-paper-scissors system


Graph-Adaptive Activation Functions for Graph Neural Networks


Graph-Aligned Random Partition Model (GARP)


Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning


Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series


Graph-Aware Contrasting for Multivariate Time-Series Classification


Graph-Aware Evolutionary Algorithms for Influence Maximization


Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers


Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images


Graph-Based DDoS Attack Detection in IoT Systems with Lossy Network


Graph-Based Equilibrium Metrics for Dynamic Supply-Demand Systems with Applications to Ride-sourcing Platforms


Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging


Graph-Based Object Classification for Neuromorphic Vision Sensing


Graph-Based Parallel Large Scale Structure from Motion


Graph-Based Pulse Representation for Diverse Quantum Control Hardware


Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering


Graph-Based Reductions for Parametric and Weighted MDPs


Graph-Based Representation Learning of Neuronal Dynamics and Behavior


Graph-Based Semi-Supervised Conditional Random Fields For Spoken Language Understanding Using Unaligned Data


Graph-Based Shape Analysis Beyond Context-Freeness


Graph-Based Similarity of Neural Network Representations


Graph-Embedded Subspace Support Vector Data Description


Graph-Embedding Empowered Entity Retrieval


Graph-Enabled Fast MCMC Sampling with an Unknown High-Dimensional Prior Distribution


Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation


Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation


Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning


Graph-Free Knowledge Distillation for Graph Neural Networks


Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncoders


Graph-Instructed Neural Networks for Sparse Grid-Based Discontinuity Detectors


Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification


Graph-MLP: Node Classification without Message Passing in Graph


Graph-SCP: Accelerating Set Cover Problems with Graph Neural Networks


Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems


Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph


Graph-Structured Data Analysis of Component Failure in Autonomous Cargo Ships Based on Feature Fusion


Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization


Graph-Text Multi-Modal Pre-training for Medical Representation Learning


Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image Classification


Graph-accelerated Markov Chain Monte Carlo using Approximate Samples


Graph-based Algorithms for Linear Computation Coding


Graph-based Alignment and Uniformity for Recommendation


Graph-based Change Point Detection for Functional Data


Graph-based Clustering for Detecting Semantic Change Across Time and Languages


Graph-based Deep Learning for Communication Networks: A Survey


Graph-based Filtering of Out-of-Vocabulary Words for Encoder-Decoder Models


Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling


Graph-based Generative Face Anonymisation with Pose Preservation


Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval


Graph-based Incident Aggregation for Large-Scale Online Service Systems


Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification


Graph-based Keyword Planning for Legal Clause Generation from Topics


Graph-based Knowledge Distillation: A survey and experimental evaluation


Graph-based Modeling of Online Communities for Fake News Detection


Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting


Graph-based Multi-sensor Fusion for Consistent Localization of Autonomous Construction Robots


Graph-based Nearest Neighbor Search: From Practice to Theory


Graph-based Neural Architecture Search with Operation Embeddings


Graph-based Person Signature for Person Re-Identifications


Graph-based Polyphonic Multitrack Music Generation


Graph-based Recommendation for Sparse and Heterogeneous User Interactions


Graph-based Semantical Extractive Text Analysis


Graph-based Semi-Supervised & Active Learning for Edge Flows


Graph-based Semi-supervised Learning: A Comprehensive Review


Graph-based Semi-supervised Local Clustering with Few Labeled Nodes


Graph-based Simultaneous Coverage and Exploration Planning for Fast Multi-robot Search


Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction


Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects


Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks


Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting


Graph-based Topology Reasoning for Driving Scenes


Graph-based Uncertainty Metrics for Long-form Language Model Outputs


Graph-based View Motion Planning for Fruit Detection


Graph-based Village Level Poverty Identification


Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations


Graph-based clustering of gamma-ray bursts


Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems


Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models


Graph-enhanced Large Language Models in Asynchronous Plan Reasoning


Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution


Graph-guided random forest for gene set selection


Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation


Graph-level Anomaly Detection via Hierarchical Memory Networks


Graph-level Representation Learning with Joint-Embedding Predictive Architectures


Graph-level representations using ensemble-based readout functions


Graph-of-Thought: Utilizing Large Language Models to Solve Complex and Dynamic Business Problems


Graph-of-Tweets: A Graph Merging Approach to Sub-event Identification


Graph-theoretic approach to Bell experiments with low detection efficiency


Graph-theoretical approach to robust 3D normal extraction of LiDAR data


Graph-theoretical optimization of fusion-based graph state generation


Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs


Graph-to-Graph Transformer for Transition-based Dependency Parsing


Graph-to-Sequence Learning using Gated Graph Neural Networks


Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem


Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning


Graph2Kernel Grid-LSTM: A Multi-Cued Model for Pedestrian Trajectory Prediction by Learning Adaptive Neighborhoods


Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations


Graph2Pix: A Graph-Based Image to Image Translation Framework


Graph4J -- A computationally efficient Java library for graph algorithms


GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving


GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation


GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction


GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph


GraphAge: Unleashing the power of Graph Neural Network to Decode Epigenetic Aging


GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs


GraphAr: An Efficient Storage Scheme for Graph Data in Data Lakes


GraphArena: Benchmarking Large Language Models on Graph Computational Problems


GraphAttacker: A General Multi-Task GraphAttack Framework


GraphAvatar: Compact Head Avatars with GNN-Generated 3D Gaussians


GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU


GraphBPE: Molecular Graphs Meet Byte-Pair Encoding


GraphBridge: Towards Arbitrary Transfer Learning in GNNs


GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognition


GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs


GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs


GraphCheck: Multi-Path Fact-Checking with Entity-Relationship Graphs


GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks


GraphCoder: Enhancing Repository-Level Code Completion via Code Context Graph-based Retrieval and Language Model


GraphConfRec: A Graph Neural Network-Based Conference Recommender System


GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction


GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration


GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems


GraphEBM: Molecular Graph Generation with Energy-Based Models


GraphER: A Structure-aware Text-to-Graph Model for Entity and Relation Extraction


GraphEdit: Large Language Models for Graph Structure Learning


GraphFC: Customs Fraud Detection with Label Scarcity


GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs


GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation


GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension


GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph


GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks


GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation


GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks


GraphGPT: Graph Instruction Tuning for Large Language Models


GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion


GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software


GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation


GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation


GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation


GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks


GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems


GraphHop: An Enhanced Label Propagation Method for Node Classification


GraphIQA: Learning Distortion Graph Representations for Blind Image Quality Assessment


GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability


GraphKAN: Enhancing Feature Extraction with Graph Kolmogorov Arnold Networks


GraphKD: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation


GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis


GraphLLM: Boosting Graph Reasoning Ability of Large Language Model


GraphLearner: Graph Node Clustering with Fully Learnable Augmentation