Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs

Daniel Neil, Joss Briody, Alix Lacoste +3

In this work, we provide a new formulation for Graph Convolutional Neural Networks (GCNNs) for link prediction on graph data that addresses common challenges for biomedical knowled…