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X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-8f4c7958a3ef11baf6c6053f83fc3511@cmc.deusto.eus
DTSTART:20201104T160000Z
DTEND:20201104T170000Z
DTSTAMP:20251031T223700Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:Deep Learning and Optimal Control with Fractional Operators
DESCRIPTION:Speaker: Prof. Dr. Harbir Antil\nAffiliation: George Mason University, USA\nOrganized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg\nZoom link\nMeeting ID:  912 4704 6250 | PIN code: 429486\nAbstract. Fractional calculus and its application to anomalous diffusion has recently received a tremendous amount of attention. In complex/heterogeneous material mediums, the long-range correlations or hereditary material properties are presumed to be the cause of such anomalous behavior. Owing to the revival of fractional calculus, these effects are now conveniently modeled by fractional-order differential operators and the governing equations are reformulated accordingly. Similarly, the potential of fractional operators has been harnessed in various scientific domains like geophysical electromagnetics, imaging science, deep learning, etc. In this talk, fractional operators will be introduced and both linear and nonlinear, fractional-order differential equations will be discussed. New notions of optimal control and optimization under uncertainty will be presented. A special emphasis will be given on enriching Deep Neural Networks using fractional operators. Several applications from geophysics, imaging science, and deep learning will be presented.\n
URL:https://cmc.deusto.eus/events-calendar/deep-learning-and-optimal-control-with-fractional-operators/
CATEGORIES:FAU CAA Seminar,Seminar/Talk
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