Junchi Yu

Recognizing Predictive Substructures With Subgraph Information Bottleneck

2021 · IEEE Transactions on Pattern Analysis and Machine Intelligence

The emergence of Graph Convolutional Network (GCN) has greatly boosted the progress of graph learning. However, two disturbing factors, noise and redundancy in graph data, and lack of interpretation for prediction results, impede further development …

Towards the Explanation of Graph Neural Networks in Digital Pathology with Information Flows

2021 · arXiv (Cornell University)

As Graph Neural Networks (GNNs) are widely adopted in digital pathology, there is increasing attention to developing explanation models (explainers) of GNNs for improved transparency in clinical decisions. Existing explainers discover an explanatory subgraph relevant …