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Graph Attention

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Showing 651–675 of 1088 papers

TitleStatusHype
Reasoning Over Semantic-Level Graph for Fact Checking—0
Reconstructing Event Regions for Event Extraction via Graph Attention Networks—0
Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning—0
Reducing Over-smoothing in Graph Neural Networks Using Relational Embeddings—0
Attentive Graph Enhanced Region Representation Learning—0
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks—0
Reinforcement Learning with Graph Attention for Routing and Wavelength Assignment with Lightpath Reuse—0
Relation-aware Graph Attention Model With Adaptive Self-adversarial Training—0
Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection—0
Relationship-based Neural Baby Talk—0
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention—0
Representation Learning to Advance Multi-institutional Studies with Electronic Health Record Data—0
Research on feature fusion and multimodal patent text based on graph attention network—0
Retinal Vessel Segmentation with Deep Graph and Capsule Reasoning—0
Revolutionizing TCAD Simulations with Universal Device Encoding and Graph Attention Networks—0
RGAT: A Deeper Look into Syntactic Dependency Information for Coreference Resolution—0
r-GAT: Relational Graph Attention Network for Multi-Relational Graphs—0
Robust 3D Shape Classification via Non-Local Graph Attention Network—0
Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning—0
Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks—0
SafeCast: Risk-Responsive Motion Forecasting for Autonomous Vehicles—0
Saliency Prediction with External Knowledge—0
SAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection—0
Scalable Graph Attention-based Instance Selection via Mini-Batch Sampling and Hierarchical Hashing—0
Scalable Traffic Signal Controls using Fog-Cloud Based Multiagent Reinforcement Learning—0
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