A podcast discussing the new paradigm for generative modeling using Continuous Normalizing Flows (CNFs) called Flow Matching (FM). FM offers a simulation-free approach for training CNFs by regressing vector fields of fixed conditional probability paths, which enables training CNFs at unprecedented scale and allows for the use of different probability paths.
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