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GitHub / jElhamm / Article-Deep-Learning-for-the-Gaussian-Wiretap-Channel

Simulations for the paper "Deep Learning for the Gaussian Wiretap Channel by Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder"

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jElhamm%2FArticle-Deep-Learning-for-the-Gaussian-Wiretap-Channel

Stars: 1
Forks: 0
Open Issues: 0

License: mit
Language: Python
Repo Size: 375 KB
Dependencies: 0

Created: 3 months ago
Updated: about 2 months ago
Last pushed: about 2 months ago
Last synced: about 2 months ago

Topics: custom-layers, data-communications, deep-learning, deep-learning-papers, encoder-decoder-model, jupyter-notebook, loss, matplotlib-pyplot, numpy, optimizer, pandas, paper, python, scipy, simulations, sklearn-preprocessing, tensorflow, tensorflow-keras-model, training, wiretap

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