Keynote

Leveraging large-scale data and accelerated computing systems, statistical learning has led to significant paradigm shifts in many scientific disciplines. Grand challenges in science have been tackled with exciting synergy between disciplinary science, physics-based simulations via high-performance computing, and powerful learning methods. In this talk, Fei Sha will describe two vignettes of our research in this theme: probabilistic generative AI technology for uncertainty quantification, and closure modeling. He will also demonstrate how those technologies can be effectively applied to weather and climate, addressing crucial problems in those areas.

Note: The research work presented in this talk is based on joint and interdisciplinary research work of several teams at Google Research.