Pytorch implementation of Relational GCN for node classification

Graph Convolution Neural Networks for Mutagenic Molecule Detection

Explainable Graph Neural Networks (XGNNs) and Reinforcement Learning (RL) techniques for graph generation and optimization tasks. The project aims to explore and validate the use of explainable AI for creating interpretable graph structures.