A PyTorch Implementation of bilateral-GGNN for Graph Classification
This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated Graph Sequence Neural Networks by Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel.
This implementation focuses on the Graph Level output, which hasn't been exploiting from the other code base. In concrete, we focus the Graph Classification task, which requires the Graph Level output to be implemented.