Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on Deep Graph Library (DGL)
Alternative PyTorch-Geometric implementation
Heterogeneous Graph Transformer is a graph neural network architecture that can deal with large-scale heterogeneous and dynamic graphs.
You can see our WWW 2020 paper “Heterogeneous Graph Transformer” for more details.
This implementation of HGT is based on Deep Graph Library (DGL) API, following their tutorial
TODO: Current DGL example use random input node feature. We’ll later add other benchmark using meaningful input node features.