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Graph Neural Network

Papers

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Showing 2601–2625 of 3598 papers

TitleStatusHype
Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation—0
TransferLight: Zero-Shot Traffic Signal Control on any Road-Network—0
Transferring Graph Neural Networks for Soft Sensor Modeling using Process Topologies—0
Transformers meet Neural Algorithmic Reasoners—0
Transportation Scenario Planning with Graph Neural Networks—0
Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition—0
Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning—0
Trigger-GNN: A Trigger-Based Graph Neural Network for Nested Named Entity Recognition—0
Triplet Edge Attention for Algorithmic Reasoning—0
TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs—0
True or False? Detecting False Information on Social Media Using Graph Neural Networks—0
Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning—0
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature—0
Two-level Graph Network for Few-Shot Class-Incremental Learning—0
Two-level Graph Neural Network—0
Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models—0
Two-Stage Stance Labeling: User-Hashtag Heuristics with Graph Neural Networks—0
Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems—0
UBER-GNN: A User-Based Embeddings Recommendation based on Graph Neural Networks—0
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks—0
Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation—0
Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion—0
Uncertainty-Aware Robust Learning on Noisy Graphs—0
Uncertainty-Aware Transient Stability-Constrained Preventive Redispatch: A Distributional Reinforcement Learning Approach—0
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
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