Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy

Related tags

Deep LearningDrugRankGCN_NumPy
Overview

About this Project

  • When I was teaching myself machine learning, I wanted to make sure that I fully understood the logic and backpropagation calculus behind all of the network architectures and training techniques that I implemented.
  • This project uses pure Python and NumPy to implement Graph Convolutional Networks with global and hierarchical architectures as well as various graph pooling methods.
  • The models were trained to classify compounds using the Adadelta algorithm for gradient descent.
Owner
Noah Getz
Noah Getz
GitHub Repository
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