braun-steven/simple-einet
An implementation of EinsumNetworks in PyTorch.
This project offers an implementation of Einsum Networks, a type of probabilistic model, for machine learning practitioners. It allows you to train models for tasks like classifying images (like the MNIST dataset) or understanding complex data relationships. You provide a dataset, and it produces a trained model that can classify new data or generate samples that resemble your original data. This is for machine learning researchers and data scientists working with probabilistic models.
Use this if you need to build and train generative or discriminative probabilistic models, especially for image classification or sampling from complex data distributions.
Not ideal if you are not familiar with machine learning concepts and probabilistic models, or if you're looking for a simple, out-of-the-box solution without customizability.
Stars
23
Forks
11
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 26, 2026
Commits (30d)
0
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