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.
AUTHORS
Written by
Marton Havasi
Peter Holderrieth
Neta Shaul
Brian Karrer
Ricky Chen
Heli Ben Hamu
Publisher
arXiv
Research Topics
Core Machine Learning
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