SOTAVerified

Graph Neural Network

Papers

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Showing 2626–2650 of 3598 papers

TitleStatusHype
Understanding and Modeling Job Marketplace with Pretrained Language Models—0
Understanding GNNs for Boolean Satisfiability through Approximation Algorithms—0
Understanding Human Innate Immune System Dependencies using Graph Neural Networks—0
Understanding the Performance of Learning Precoding Policy with GNN and CNNs—0
Unifews: Unified Entry-Wise Sparsification for Efficient Graph Neural Network—0
Unified Graph Structured Models for Video Understanding—0
Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting—0
UniGO: A Unified Graph Neural Network for Modeling Opinion Dynamics on Graphs—0
Unlearnable Graph: Protecting Graphs from Unauthorized Exploitation—0
Unpaired Image Captioning by Image-level Weakly-Supervised Visual Concept Recognition—0
Unsupervised Domain Adaptation with Global and Local Graph Neural Networks in Limited Labeled Data Scenario: Application to Disaster Management—0
Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization—0
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models—0
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models—0
Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information—0
Unsupervised Training for Neural TSP Solver—0
Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies—0
Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs—0
Up-sampling-only and Adaptive Mesh-based GNN for Simulating Physical Systems—0
Urban Traffic Forecasting with Integrated Travel Time and Data Availability in a Conformal Graph Neural Network Framework—0
Using Graph Neural Networks for Program Termination—0
Using Graph Neural Networks to Predict Local Culture—0
Using Graph Neural Networks to Reconstruct Ancient Documents—0
UT-GraphCast Hindcast Dataset: A Global AI Forecast Archive from UT Austin for Weather and Climate Applications—0
Utilizing Graph Neural Networks for Effective Link Prediction in Microservice Architectures—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1air0S1—Unverified