Graph Transformer是一种将Transformer架构应用于图结构数据的特殊神经网络模型。该模型通过融合图神经网络(GNNs)的基本原理与Transformer的自注意力机制 ...

To tackle these challenges, we propose an edge-enhanced heterogeneous graph Transformer with priority-based feature aggregation for multi-modal trajectory prediction. Specifically, a new edge-enhanced ...

Transformers have been the foundation of large language models (LLMs), and recently, their application has expanded to search problems in graphs, a foundational domain in computational logic, planning ...

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In this work, we propose a novel event-based motion segmentation algorithm using a Graph Transformer Neural Network, dubbed GTNN. Our proposed algorithm processes event streams as 3D graphs by a ...

SAG-ViT is a novel framework designed to enhance Vision Transformers (ViT) with scale-awareness and refined patch-level feature embeddings. Traditional ViTs rely on fixed-sized patches extracted ...