Jhomanik/Optimal-Flow-Matching
The official repository for the paper "Optimal Flow Matching: Learning Straight Trajectories in Just One Step" (NeurIPS 2024)
This is a developer tool for researchers working in machine learning and optimal transport. It provides code to implement a new method called Optimal Flow Matching (OFM), which efficiently learns direct paths between different data distributions using a single step. Researchers who develop or apply advanced machine learning models for tasks like generative modeling or data transformation would find this useful.
110 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or practitioner exploring novel methods for generative modeling or efficient data distribution transformation, particularly those involving optimal transport.
Not ideal if you are looking for a plug-and-play solution for data analysis or a tool for general machine learning tasks without deep expertise in flow matching or optimal transport.
Stars
110
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Dec 19, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/Jhomanik/Optimal-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/flow-matching
Annotated Flow Matching paper