Each message-passing step covers immediate neighbors, and additional layers capture a wider network context, enabling a comprehensive understanding of graph structures. TF-GNN overview Fig. 2: Layers ...

The team proposed a Graph-Segmenter, including a Graph Transformer and a Boundary-aware Attention module, which is an effective network for simultaneously modeling the more profound relation ...

We can see her presenting on simulations and learning tasks as graphs, with an emphasis on two models: message passing graph neural networks, and graph transformers.