sail-sg/DiffMemorize
[TMLR 2025] On Memorization in Diffusion Models
This project provides tools for researchers and machine learning engineers to investigate how and why diffusion models 'memorize' training data. It allows you to input image datasets like CIFAR-10 or ImageNet, train diffusion models under various conditions, and then measure the extent to which these models reproduce specific training examples rather than generating novel images. The outputs are metrics and generated images that reveal memorization patterns.
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Use this if you are a researcher or ML engineer studying the privacy implications, robustness, or generalization capabilities of diffusion models and need to empirically quantify memorization.
Not ideal if you are looking to simply train a diffusion model for image generation or apply one to a creative task, as this tool is focused on the analytical study of memorization.
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31
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3
Language
Python
License
MIT
Category
Last pushed
Oct 05, 2023
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