mandt-lab/PSLD
Official Implementation of the paper: A Complete Recipe for Diffusion Generative Models
This project offers a comprehensive method for creating new diffusion generative models. It takes training image datasets (like CIFAR-10 or CelebA) and outputs high-quality synthetic images, outperforming existing models. This tool is designed for machine learning researchers and practitioners focused on generative AI and image synthesis.
No commits in the last 6 months.
Use this if you are an AI researcher or practitioner looking to develop advanced generative models for creating realistic images with improved sample quality and a principled approach to diffusion process design.
Not ideal if you are looking for a plug-and-play image generation tool without diving into model architecture and training configurations.
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Language
Python
License
MIT
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Last pushed
Nov 01, 2024
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