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Graph Attention

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Showing 626–650 of 1088 papers

TitleStatusHype
Task-Driven Graph Attention for Hierarchical Relational Object Navigation—0
TC-GAT: Graph Attention Network for Temporal Causality Discovery—0
TeMO: Towards Text-Driven 3D Stylization for Multi-Object Meshes—0
Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection—0
The Graph feature fusion technique for speaker recognition based on wav2vec2.0 framework—0
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation—0
Time-aware Relational Graph Attention Network for Temporal Knowledge Graph Embeddings—0
TOFG: A Unified and Fine-Grained Environment Representation in Autonomous Driving—0
Topological Cycle Graph Attention Network for Brain Functional Connectivity—0
Topological Neural Networks: Mitigating the Bottlenecks of Graph Neural Networks via Higher-Order Interactions—0
Topology-Aware Graph Neural Network-based State Estimation for PMU-Unobservable Power Systems—0
Topology-Aware Pooling via Graph Attention—0
Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection—0
Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention—0
Towards Context-Aware Code Comment Generation—0
Towards Explainable Graph Neural Networks for Neurological Evaluation on EEG Signals—0
Towards Overcoming False Positives in Visual Relationship Detection—0
Towards understanding how attention mechanism works in deep learning—0
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method—0
Triplet Edge Attention for Algorithmic Reasoning—0
TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems—0
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees—0
Two Stream Scene Understanding on Graph Embedding—0
U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction—0
UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs—0
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