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Graph Neural Network

Papers

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Showing 2101–2150 of 3598 papers

TitleStatusHype
One Model Fits All: Cross-Region Taxi-Demand Forecasting—0
Hyperdimensional Representation Learning for Node Classification and Link Prediction—0
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods—0
Online Algorithm for Node Feature Forecasting in Temporal Graphs—0
Online Frequency Scheduling by Learning Parallel Actions—0
Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network—0
On Locality in Graph Learning via Graph Neural Network—0
On Node Features for Graph Neural Networks—0
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks—0
On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs—0
On Self-Distilling Graph Neural Network—0
On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problem—0
On Structural Expressive Power of Graph Transformers—0
On the combination of graph data for assessing thin-file borrowers' creditworthiness—0
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization—0
On the Effect of Input Perturbations for Graph Neural Networks—0
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks—0
On the Interplay of Subset Selection and Informed Graph Neural Networks—0
On the Limit of Explaining Black-box Temporal Graph Neural Networks—0
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods—0
On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning—0
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network—0
Operational Wind Speed Forecasts for Chile's Electric Power Sector Using a Hybrid ML Model—0
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods—0
Opinion de-polarization of social networks with GNNs—0
Optical Quantum Sensing for Agnostic Environments via Deep Learning—0
Optimality of Message-Passing Architectures for Sparse Graphs—0
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Graph Neural Imitation Learning—0
Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search—0
Optimal Wireless Resource Allocation with Random Edge Graph Neural Networks—0
Optimization of Image Embeddings for Few Shot Learning—0
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features—0
Ordered Topological Deep Learning: a Network Modeling Case Study—0
Ordinary differential equations on graph networks—0
ORID: Organ-Regional Information Driven Framework for Radiology Report Generation—0
Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion—0
Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction—0
Overcoming Class Imbalance: Unified GNN Learning with Structural and Semantic Connectivity Representations—0
Overhead-Free Blockage Detection and Precoding Through Physics-Based Graph Neural Networks: LIDAR Data Meets Ray Tracing—0
PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning—0
Packet Routing with Graph Attention Multi-agent Reinforcement Learning—0
Pairing-based graph neural network for simulating quantum materials—0
Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks—0
PanRep: Universal node embeddings for heterogeneous graphs—0
ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels—0
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning—0
ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening—0
Partial Search in a Frozen Network is Enough to Find a Strong Lottery Ticket—0
Particle-based plasma simulation using a graph neural network—0
Partitioning Distributed Compute Jobs with Reinforcement Learning and Graph Neural Networks—0
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