varun-ml/diffusion-models-tutorial
Experiment with diffusion models that you can run on your local jupyter instances
This project helps machine learning practitioners understand and experiment with diffusion models for density estimation and data generation. It takes a conceptual understanding of diffusion models and demonstrates their application, starting with simple 2D data distributions and progressing to generating characters from the EMNIST dataset. The target user is a machine learning engineer or researcher looking to deepen their practical knowledge of generative models.
No commits in the last 6 months.
Use this if you are a machine learning practitioner keen to learn the practical implementation of diffusion models for tasks like image generation or density estimation.
Not ideal if you are looking for a ready-to-use, high-level library for production-scale generative AI applications without needing to understand the underlying mechanics.
Stars
66
Forks
12
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 27, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/varun-ml/diffusion-models-tutorial"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quantgirluk/aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
blei-lab/treeffuser
Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression...
TuftsBCB/RegDiffusion
Diffusion model for gene regulatory network inference.
yuanchenyang/smalldiffusion
Simple and readable code for training and sampling from diffusion models
chairc/Integrated-Design-Diffusion-Model
IDDM (Industrial, landscape, animate, latent diffusion), support LDM, DDPM, DDIM, PLMS, webui...