CORE MACHINE LEARNING

Flow Matching Guide and Code

December 10, 2024

Abstract

Flow Matching (FM) is a recent framework for generative modeling that has achieved state-of-the-art performance across various domains, including image, video, audio, speech, and biological structures. This guide offers a comprehensive and self-contained review of FM, covering its mathematical foundations, design choices, and extensions. By also providing a PyTorch package featuring relevant examples (e.g., image and text generation), this work aims to serve as a resource for both novice and experienced researchers interested in understanding, applying and further developing FM.

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AUTHORS

Written by

Yaron Lipman

Marton Havasi

Peter Holderrieth

Neta Shaul

Matt Le

Brian Karrer

Ricky Chen

David Lopez-Paz

Heli Ben Hamu

Itai Gat

Publisher

arXiv

Research Topics

Core Machine Learning

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