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DTSTART:19810329T020000
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DTSTART:19961027T030000
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UID:news1157@dmi.unibas.ch
DTSTAMP;TZID=Europe/Zurich:20210627T202913
DTSTART;TZID=Europe/Zurich:20210604T110000
SUMMARY:Seminar in Numerical Analysis: Ivan Dokmanić (Universität Basel)
DESCRIPTION:This talk will be an overview of my group's research between de
 ep learning and inverse problems. I will first describe the current (?) st
 ate of the field and then present a medley of our results\, including 1) a
  neural network architecture for wave-based inverse problems derived from 
 Fourier integral operators\; 2) an approach to nonlinear traveltime tomogr
 aphy based on neural priors\; and 3) provably injective neural networks th
 at are universal approximators of probability measures supported on low-di
 mensional manifolds. My secret hope is to spark discussions that could evo
 lve to collaborations.\\r\\nFor further information about the seminar\, pl
 ease visit this webpage [t3://page?uid=1115].
X-ALT-DESC:<p>This talk will be an overview of my group's research between 
 deep learning and inverse problems. I will first describe the current (?) 
 state of the field and then present a medley of our results\, including 1)
  a neural network architecture for wave-based inverse problems derived fro
 m Fourier integral operators\; 2) an approach to nonlinear traveltime tomo
 graphy based on neural priors\; and 3) provably injective neural networks 
 that are universal approximators of probability measures supported on low-
 dimensional manifolds. My secret hope is to spark discussions that could e
 volve to collaborations.</p>\n<p>For further information about the seminar
 \, please visit this <a href="t3://page?uid=1115" title="Opens internal li
 nk in current window">webpage</a>.</p>
DTEND;TZID=Europe/Zurich:20210604T120000
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