# pytorch-rbm

**Repository Path**: haohan1997/pytorch-rbm

## Basic Information

- **Project Name**: pytorch-rbm
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2021-04-11
- **Last Updated**: 2024-01-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Restricted Boltzmann Machines (RBMs) in PyTorch

> **Author:** [Gabriel Bianconi](http://www.gabrielbianconi.com/)

## Overview

This project implements Restricted Boltzmann Machines (RBMs) using PyTorch (see `rbm.py`). Our implementation includes momentum, weight decay, L2 regularization, and CD-*k* contrastive divergence. We also provide support for CPU and GPU (CUDA) calculations.

In addition, we provide an example file applying our model to the MNIST dataset (see `mnist_dataset.py`). The example trains an RBM, uses the trained model to extract features from the images, and finally uses a SciPy-based logistic regression for classification. It achieves 92.8% classification accuracy (this is obviously not a cutting-edge model).