Prof. Stephan Mandt

(University of California, Irvine)
hosted by Machine Learning Group of Prof. Marius Kloft

"Scientific Inference with Diffusion Generative Models"

Diffusion models have transformed generative modeling in various domains such as vision and language. But can they serve as tools for scientific inference? In this talk, Stephan Mandt presents a perspective that reframes diffusion models as Bayesian solvers for scientific inverse problems - involving a noisy measurement process - with applications ranging from climate modeling to astrophysical imaging.

Bio: Stephan Mandt is an Associate Professor of Computer Science and Statistics at the University of California, Irvine. His research contributes to the foundations and applications of generative AI, with a focus on generative modeling of 2D, 3D, and sequential data, compression, resource-efficient learning, inference algorithms, and AI-driven scientific discovery. He is a Chan Zuckerberg Investigator and AI Resident and has received the NSF CAREER Award, the UCI ICS Mid-Career Excellence in Research Award, and a Kavli Fellowship. Before UCI, he led the machine learning group at Disney Research and held postdoctoral positions at Princeton and Columbia. Stephan frequently serves as a Senior Area Chair for NeurIPS, ICML, and ICLR and was most recently Program Chair for AISTATS 2024 and General Chair for AISTATS 2025.

Time:	Wednesday, 17.09.2025, 15:30
Place:	Room 48/208

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