https://github.com/refraction-ray/rbm-mcmc

The project explores restricted Boltzmann machine and its potential role in statistical mechanics
https://github.com/refraction-ray/rbm-mcmc

machine-learning monte-carlo physics rbm

Last synced: 14 days ago
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The project explores restricted Boltzmann machine and its potential role in statistical mechanics

• Host: GitHub
• URL: https://github.com/refraction-ray/rbm-mcmc
• Owner: refraction-ray
• License: mit
• Created: 2018-04-24T02:13:29.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-04-30T14:04:10.000Z (almost 7 years ago)
• Last Synced: 2025-01-06T02:49:56.289Z (about 1 month ago)
• Topics: machine-learning, monte-carlo, physics, rbm
• Language: Jupyter Notebook
• Homepage:
• Size: 173 KB
• Stars: 0
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# RBM-MCMC

## Introduction

This project is designed for an integrated study on the intersection between condensed matter physics and machine learning. Specifically, we pay attention to energy based models (RBM for example) and how can such models play vital roles in statistical mechanics (ensemble probability distribution for example).

We need two types of tools, **classical Markov chain Monte Carlo** method and **restricted Boltzmann machines** to make our ideas into practice.

## Usage

See `demo.ipynb` for a general idea on usage. And use `help()` in python anytime you need help.