2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.NE2022★ 2 cited
Spiking GATs: Learning Graph Attentions via Spiking Neural Network
Beibei Wang, Bo Jiang
Graph Attention Networks (GATs) have been intensively studied and widely used in graph data learning tasks. Existing GATs generally adopt the self-attention mechanism to conduct gr…
cs.LG2022
Generalizing Aggregation Functions in GNNs:High-Capacity GNNs via Nonlinear Neighborhood Aggregators
Beibei Wang, Bo Jiang
Graph neural networks (GNNs) have achieved great success in many graph learning tasks. The main aspect powering existing GNNs is the multi-layer network architecture to learn the n…