lebellig/flow-matching
Annotated Flow Matching paper
This project helps researchers and machine learning engineers explore and understand advanced generative modeling techniques. It takes as input a dataset and provides a trained model that can generate new, similar data samples. This is ideal for those interested in the cutting edge of data synthesis and probabilistic modeling.
229 stars. No commits in the last 6 months.
Use this if you are a researcher or ML engineer studying generative models and want to understand how Flow Matching for Generative Modeling works by experimenting with an implementation.
Not ideal if you need a production-ready generative model or an official implementation of the Flow Matching paper.
Stars
229
Forks
14
Language
Jupyter Notebook
License
—
Category
Last pushed
Sep 14, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/lebellig/flow-matching"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
AngeClementAkazan/Sequential-FeatureForestFlow
This repository contains the code source of the Heterogeneous Sequential Feature Forest Flow...
AlejandroMllo/action_flow_matching
Code for the paper "Action Flow Matching for Continual Robot Learning" presented at Robotics:...
dsgiitr/flux-watermarking
Official Implementation of the paper WMARK@ICLR Detection Limits and Statistical Separability of...
ericbill21/FOCUS
Official codebase for FOCUS: Optimal Control Meets Flow Matching: A Principled Route to...
lebellig/discrete-fm
Educational implementation of the Discrete Flow Matching paper