40 citations · 114 across the 12 of their papers we have counts for
5 papers · 1 filter
Reliable and Compact Graph Fine-tuning via GraphSparse Prompting
Bo Jiang, Hao Wu, Beibei Wang +2
Recently, graph prompt learning has garnered increasing attention in adapting pre-trained GNN models for downstream graph learning tasks. However, existing works generally conduct…
Graph Edge Representation via Tensor Product Graph Convolutional Representation
Bo Jiang, Sheng Ge, Ziyan Zhang +3
Graph Convolutional Networks (GCNs) have been widely studied. The core of GCNs is the definition of convolution operators on graphs. However, existing Graph Convolution (GC) operat…
A Unified Graph Selective Prompt Learning for Graph Neural Networks
Bo Jiang, Hao Wu, Ziyan Zhang +2
In recent years, graph prompt learning/tuning has garnered increasing attention in adapting pre-trained models for graph representation learning. As a kind of universal graph promp…
Context-Aware Graph Attention Networks
Bo Jiang, Leiling Wang, Jin Tang +1
Graph Neural Networks (GNNs) have been widely studied for graph data representation and learning. However, existing GNNs generally conduct context-aware learning on node feature re…
D-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios
Zhengping Che, Guangyu Li, Tracy Li +7
Driving datasets accelerate the development of intelligent driving and related computer vision technologies, while substantial and detailed annotations serve as fuels and powers to…