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Graph Attention

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Showing 826–850 of 1088 papers

TitleStatusHype
Foresight of Graph Reinforcement Learning Latent Permutations Learnt by Gumbel Sinkhorn Network—0
FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity MappingCode0
Contrastive Document Representation Learning with Graph Attention Networks—0
Context-aware Reranking with Utility Maximization for Recommendation—0
Urban traffic dynamic rerouting framework: A DRL-based model with fog-cloud architecture—0
Scalable Traffic Signal Controls using Fog-Cloud Based Multiagent Reinforcement Learning—0
Multi-Relation Aware Temporal Interaction Network EmbeddingCode0
Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks—0
Multi-scale speaker embedding-based graph attention networks for speaker diarisation—0
EBSD Grain Knowledge Graph Representation Learning for Material Structure-Property Prediction—0
Fast fixed-backbone protein sequence and rotamer design—0
Learning to Solve an Order Fulfillment Problem in Milliseconds with Edge-Feature-Embedded Graph Attention—0
Personalized PageRank meets Graph Attention Networks—0
Time-aware Relational Graph Attention Network for Temporal Knowledge Graph Embeddings—0
Graph Reasoning with Context-Aware Linearization for Interpretable Fact Extraction and Verification—0
wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction—0
Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference—0
r-GAT: Relational Graph Attention Network for Multi-Relational Graphs—0
DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control—0
Graph Attention Network Based Single-Pixel Compressive Direction of Arrival Estimation—0
Graph Attention Layer Evolves Semantic Segmentation for Road Pothole Detection: A Benchmark and Algorithms—0
Soft Hierarchical Graph Recurrent Networks for Many-Agent Partially Observable Environments—0
On the Significance of Question Encoder Sequence Model in the Out-of-Distribution Performance in Visual Question Answering—0
GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations—0
Graph Attention MLP with Reliable Label Utilization—0
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