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Deepcode-Interpretability

Overview

This repository contains the codes for the paper "Interpreting Deepcode, a learned feedback code". It is a non-linear interpretable model for AWGN channel with feedback.

Structure

noiseless_feedback

The noiseless_feedback folder contains:

  • deepcode - Implementation of the Deepcode using Pytorch based on Tensorflow Deepcode.
  • interpretable - Interpretable model based on Deepcode: 5 hidden states (encoder + decoder) / 7 hidden states (encoder)
  • equivalent - Contains equivalent expression of interpretable model

noisy_feedback

The noisy_feedback folder contains the model when the feedback is noisy.

Prerequisites

Python environment:

  • Python 3.10.8
  • numpy: 1.23.4
  • pytorch: 1.12.1

original TensorFlow Deepcode: https://github.com/hyejikim1/Deepcode

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