CFG based program similarity using Graph Neural Networks
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Updated
Mar 21, 2023 - Python
CFG based program similarity using Graph Neural Networks
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.
An implementation from scratch of Graph Convolutional Networks (GCN) using Numpy
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
Official PyTorch Implementation of paper 'Edge-Based Graph Neural Networks for Cell-Graph Modeling and Prediction'
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