Let's summarize various implementation codes of GCN by compounds

Introduction

I implemented GCN based on the paper "Convolutional Networks on Graphs for Learning Molecular Fingerprints" (https://arxiv.org/abs/1509.09292) by David Duvenaud et al., Which was the forerunner of GCN by compounds, and tried to play with it. , The original treatise was developed in a minor library called Autograd, and it was difficult to modify it as it is, so a memo when I examined various other open source implementation code

Examined implementation code

--Implementation of the author of the treatise (original)

Where to look

What I investigated this time is not the coding of atoms and bonds, but the part of how to build a neural network.

Implementation of the author of the treatise (original)

--DL framework used: Autograd

DeepChem --DL framework used: TensorFlow

Chainer-Chemistory --DL framework used: Chainer-Chemistory

OpenChem --DL framework used: PyTorch

in conclusion

――It turned out that there are various ways to implement one method. --Chainer-I like the Chemistry implementation the most. However, since I want to use PyTorch as the framework, I would like to implement it with PyTorch while referring to the source of Chainer-Chemistory.

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