Hao-Wei Hsu

TreeXGNN: can gradient-boosted decision trees help boost heterogeneous graph neural networks?

Graph neural networks are a promising deep learning method that can apply graph structures to various tasks. In real-world scenarios, we often have heterogeneous graphs, wherein different node and edge types capture complex interactions between nodes. High-dimensional node features provide rich info…