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X-ORIGINAL-URL:https://cmc.deusto.eus/
X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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UID:MEC-38be5418a8e2601443030c8cba989324@cmc.deusto.eus
DTSTART:20211008T140000Z
DTEND:20211008T150000Z
DTSTAMP:20251031T214200Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:On solving/learning differential equations with kernels
DESCRIPTION:Speaker: Prof. Dr. Houman Owhadi\nAffiliation: Caltech (USA)\nOrganized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany)\nZoom meeting link\nMeeting ID: 686 4453 8133 | PIN code: 603054\nAbstract. We present a simple, rigorous, and unified framework for solving and learning (possibly nonlinear) differential equations (PDEs and ODEs) using the framework of Gaussian processes/kernel methods.\nFor PDEs the proposed approach: (1) provides a natural generalization of collocation kernel methods to nonlinear PDEs and Inverse Problems; (2) has guaranteed convergence for a very general class of PDEs, and comes equipped with a path to compute error bounds for specific PDE approximations; (3) inherits the state-of-the-art computational complexity of linear solvers for dense kernel matrices. For ODEs, we illustrate the efficacy of the proposed approach by extrapolating weather/climate time series obtained from satellite data and highlight the importance of using adapted/learned kernels.\nParts of this talk are joint work with Yifan Chen, Boumediene Hamzi, Bamdad Hosseini, Romit Maulik, Florian Schäfer, Clint Scovel and Andrew Stuart.\nThis event on LinkedIn\n
URL:https://cmc.deusto.eus/events-calendar/on-solving-learning-differential-equations-with-kernels/
CATEGORIES:FAU DCN-AvH Seminar,Seminar/Talk
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