AmanPriyanshu/Deep-Belief-Networks-in-PyTorch
The aim of this repository is to create RBMs, EBMs and DBNs in generalized manner, so as to allow modification and variation in model types.
This is a developer's tool for building and experimenting with deep learning models called Restricted Boltzmann Machines (RBMs) and Deep Belief Networks (DBNs). It allows you to feed in data, train these models, and then observe how well they can reconstruct the original inputs, demonstrating their ability to learn underlying patterns. It's designed for machine learning researchers and engineers who want to implement and modify these specific types of generative models.
No commits in the last 6 months.
Use this if you are a machine learning researcher or developer focusing on generative models and want a flexible PyTorch implementation of RBMs and DBNs to build upon or customize.
Not ideal if you are an end-user looking for a pre-built application to solve a specific problem without needing to write or modify deep learning code.
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Language
Python
License
MIT
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Last pushed
Sep 22, 2024
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