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DTSTAMP:20241120T082410Z
LOCATION:HG F 30 Audi Max
DTSTART;TZID=Europe/Stockholm:20240603T103000
DTEND;TZID=Europe/Stockholm:20240603T112000
UID:submissions.pasc-conference.org_PASC24_sess106_key101@linklings.com
SUMMARY:IK01 - Machine Learning for Accelerating Simulation and Scientific
  Computing
DESCRIPTION:Keynote\n\nFei Sha (Google Research)\n\nLeveraging large-scale
  data and accelerated computing systems, statistical learning has led to s
 ignificant paradigm shifts in many scientific disciplines. Grand challenge
 s in science have been tackled with exciting synergy between disciplinary 
 science, physics-based simulations via high-performance computing, and pow
 erful 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.<br /><br /><em>Note: The rese
 arch work presented in this talk is based on joint and interdisciplinary r
 esearch work of several teams at Google Research.</em>\n\nSession Chair: S
 iddhartha Mishra (ETH Zurich)
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