Zusammenfassung für den Vortrag am 23.03.2023 (17:00 Uhr)
Math Machine Learning seminar MPI MIS + UCLADohyun Kwon (University of Wisconsin-Madison)
Convergence of score-based generative modeling
23.03.2023, 17:00 Uhr,nur Video-Broadcast
Score-based generative models and diffusion probabilistic models
have exhibited exceptional performance in various applications. A natural
question that arises is whether the distribution generated by the model is
closely aligned with the given data distribution. In this talk, we will
explore an upper bound of the Wasserstein distance between these two
distributions. Based on the theory of optimal transport, we guarantee that
the framework can approximate data distributions in the space of
probability measures equipped with the Wasserstein distance. This talk is
based on joint work with Ying Fan and Kangwook Lee (UW-Madison).
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