volagold/fce-2d
Flow Contrastive Estimation (FCE) PyTorch Implementation on 2D data
This project helps machine learning practitioners more effectively estimate complex probability distributions in 2D data. It takes in 2D datasets and produces a learned energy-based model (EBM) and a flow model that can represent the underlying data distribution. This is intended for researchers and engineers working on generative models and density estimation tasks.
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Use this if you need a robust method to estimate the probability density of complex 2D data distributions where traditional methods struggle due to intractable normalizing constants.
Not ideal if you are working with high-dimensional data or if you need a solution for non-generative machine learning tasks.
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11
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Language
Python
License
MIT
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Last pushed
May 20, 2022
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