is0383kk/Pytorch_VAE-GMM
Implementation of mutual learning model between VAE and GMM.
This project helps researchers and machine learning practitioners analyze complex datasets by combining the strengths of Variational Auto-Encoders (VAEs) and Gaussian Mixture Models (GMMs). It takes raw data, typically images, and processes them to reveal underlying structures and categories. The output includes improved data representations and reconstructed data samples, beneficial for understanding data patterns and generating new, similar data.
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Use this if you are working with complex data like images and need to discover hidden patterns, cluster data into natural groups, or generate new data samples that reflect learned characteristics.
Not ideal if you need a simple, off-the-shelf clustering solution or if your primary goal is basic data classification without needing to explore latent data structures or generative capabilities.
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Python
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Last pushed
Oct 08, 2025
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