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Listing the research works related to risk control based on GNN and its interpretability. 1. we can learn the application of GNN in risk control (including fraud detection). 2. For possible prediction, we can use the interpretability of GNN to explaine how can we get such results.
SMILES converted into Graphs that contains atomic information, bonding informatics. Graphs considered as input for the NN to Predict Melting Pont of Liquid Crystals (LCs)
This repository is a brief tutorial about how Graph convolutional networks and message passing networks work with example code demonstration using pytorch and torch_geometric