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RAPID: Training energy-based models through Restricted Axons and Pattern-InDuced correlations

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Alejandro Pozas-Kerstjens, Gorka Muñoz-Gil, Miguel Angel García-March, Antonio Acín, Maciej Lewenstein, and Przemyslaw R. Grzybowski

This is a repository containing the code for models with Restricted Axons and training via Pattern-InDuced correlations (RAPID), developed in the article "Efficient training of energy-based models via spin-glass control. Alejandro Pozas-Kerstjens, Gorka Muñoz-Gil, Eloy Piñol, Miguel Ángel García-March, Antonio Acín, Maciej Lewenstein, and Przemysław R. Grzybowski. arXiv:1910.01592."

All code is written in Python.

Libraries required:

Files:

  • comparison: example of use. Trains restricted Boltzmann machines using commonplace samplers and via RAPID, and computes various indicators of quality of training.

  • MNIST training: example of use. Trains an RA-RBM in the MNIST dataset.

  • rapid: contains the relevant classes.

  • utils: additional functions relevant for the example.

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RAPID: Training energy-based models through Restricted Axons and Pattern-InDuced correlations

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