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https://github.com/cossio/advrbms.jl

Last synced: 10 days ago
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Host: GitHub
URL: https://github.com/cossio/advrbms.jl
Owner: cossio
License: mit
Created: 2022-01-25T16:57:31.000Z (almost 3 years ago)
Default Branch: master
Last Pushed: 2024-09-02T15:53:56.000Z (2 months ago)
Last Synced: 2024-10-06T19:16:07.971Z (about 1 month ago)
Language: Jupyter Notebook
Size: 203 KB
Stars: 3
Watchers: 2
Forks: 1
Open Issues: 2
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.md
- Citation: CITATION.bib

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README

        # AdvRBMs Julia package

Train and sample [Restricted Boltzmann Machines](https://en.wikipedia.org/wiki/Restricted_Boltzmann_machine) (**RBMs**) in Julia, with 1st and 2nd order **adv**ersarial constraints on the weights, that promote concentratation of information about labeled features into selected hidden units.

## Installation

This package is registered. Install with:

```julia

using Pkg

Pkg.add("AdvRBMs")

```

This package does not export any symbols.

## Related packages

Implementation of standard Restricted Boltzmann Machines in Julia:

- https://github.com/cossio/RestrictedBoltzmannMachines.jl

Ising model simulations were carried out using [IsingModels.jl](https://github.com/cossio/IsingModels.jl).

# Citation

If you use this package in a publication, please cite:

* Jorge Fernandez-de-Cossio-Diaz, Simona Cocco, and Remi Monasson. "Disentangling representations in Restricted Boltzmann Machines without adversaries." [Physical Review X 13, 021003 (2023)](https://journals.aps.org/prx/abstract/10.1103/PhysRevX.13.021003).

Or you can use the included [CITATION.bib](https://github.com/cossio/RestrictedBoltzmannMachines.jl/blob/master/CITATION.bib).