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About
President
Governance
Partner Institutions
Visit
People
Management
Faculty
Postdocs
Visiting Scholars
Staff
Research
Research Groups
Courses
Seminars
Join Us
Faculty
Postdocs
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Events
Conferences
Workshops
Forum
Life @ BIMSA
Accommodation
Transportation
Facilities
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News
News
Announcement
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Qiuzhen College, Tsinghua University
Yau Mathematical Sciences Center, Tsinghua University (YMSC)
Tsinghua Sanya International  Mathematics Forum (TSIMF)
Shanghai Institute for Mathematics and  Interdisciplinary Sciences (SIMIS)
BIMSA > Seminar on Control Theory and Nonlinear Filtering Rectified Deep Neural Networks Overcome the Curse of Dimensionality When Approximating Solutions of McKean-Vlasov Stochastic Differential Equations
Rectified Deep Neural Networks Overcome the Curse of Dimensionality When Approximating Solutions of McKean-Vlasov Stochastic Differential Equations
Organizer
Shing Toung Yau
Speaker
Zeju Sun
Time
Thursday, December 21, 2023 2:30 PM - 3:00 PM
Venue
理科楼A-230
Abstract
In this talk, I will review the paper entitled ‘Rectified Deep Neural Networks Overcome the Curse of Dimensionality When Approximating Solutions of McKean-Vlasov Stochastic Differential Equations’, in which the authors prove that rectified deep neural networks do not suffer from the curse of dimensionality when approximating McKean–Vlasov SDEs in the sense that the number of parameters in the deep neural networks only grows polynomially in the space dimension d of the SDE and the reciprocal of the accuracy .
Beijing Institute of Mathematical Sciences and Applications
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