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X-WR-CALDESC:FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship
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DTSTART;TZID=Europe/Berlin:20220610T160000
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SUMMARY:Deep redatuming for PDE and inverse problems
DESCRIPTION:Speaker: Prof. Dr. Laurent Demanet\nAffiliation: MIT – Massachusetts Institute of Technology (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: 667 5616 1029 | PIN: 387887\nAbstract. Neural networks have been leveraged in non-trivial ways in the context of computational inverse problems over the past few years. In this talk, I will explain how deep nets can sometimes generate helpful “virtual” (unobserved) solutions of PDE, when all is known about the PDE is a set of other (observed) solutions. This estimation task is dubbed deep redatuming,  and extends the reach of inversion in substantive ways. I will discuss one example in particular: symmetric autoencoders, where symmetries are the driving principle behind scientific prediction. The mathematical context for this example is a ubiquitous form of “latent rank-1” structure, which has not been formalized yet, but which is found throughout nature. Joint work with Hongyu Sun, Brindha Kanniah, Pawan Bharadwaj, and Matt Li.\nThis event on LinkedIn\n
URL:https://dcn.nat.fau.eu/events/deep-redatuming-for-pde-and-inverse-problems/
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CATEGORIES:FAU DCN-AvH Seminar,Seminar/Talk
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