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Feature Extraction in DNN

This repo contains suppoting demos for [1]. The features learned by DNNs are compared with theoretical results.

  1. exp1.py: feature extraction for network with ideal expressive power
  2. exp2.py: feature extraction for network with restricted expressive power
  3. exp3.py: demo for H-score

Environments: keras 2.3.1

A more detailed illustration and Pytorch implementations can be found in this blog series.

Reference

[1] Xu, Xiangxiang, Shao-Lun Huang, Lizhong Zheng, and Gregory W. Wornell. 2022. "An Information Theoretic Interpretation to Deep Neural Networks" Entropy 24, no. 1: 135. https://doi.org/10.3390/e24010135