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Our latest work of Statistical Flow Matching (SFM) for discrete generation has been accepted to NeurIPS 2024! Check out our paper on arXiv and our code on GitHub. We applied SFM across image, text, and biological domains demonstrate its superior sampling quality and NLL on discrete tasks.
(1/4) Can we unleash the power of Riemannian Flow Matching on discrete generation? We introduce “Statistical Flow Matching (SFM)”, a novel FM framework on the manifold of parameterized probability measures inspired by information geometry. Check it out at https://t.co/7aTdwkcNvk pic.twitter.com/QoVkn1mB8I
— Chaoran Cheng (@ccr_cheng) May 28, 2024