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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
Students
Events
Conferences
Workshops
Forum
Life @ BIMSA
Accommodation
Transportation
Facilities
Tour
News
News
Announcement
Downloads
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 Natural Gradient Gaussian Filtering
Natural Gradient Gaussian Filtering
Organizer
Shing Toung Yau
Speaker
Wenhan Cao
Time
Wednesday, July 10, 2024 3:00 PM - 3:30 PM
Venue
理科楼A-304
Abstract
Recent Gaussian filtering algorithms typically involve two steps: (1) linearizing the model, and (2) performing the Kalman filter update. However, linearization often fails to adequately handle high nonlinearity, non-Gaussianity, and measurement outliers. In this work, we demonstrate that the update step in Bayesian filtering can be viewed as a variational problem. When parameterized with a Gaussian distribution, this variational problem transforms into a parameter optimization problem that can be effectively solved using natural gradient descent. This approach significantly enhances filtering accuracy in nonlinear and non-Gaussian systems, as well as in the presence of measurement outliers, while maintaining an acceptable computational burden.
Beijing Institute of Mathematical Sciences and Applications
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