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UID:83f6bb6f7cc30ab3ad4847e813599b54
DTSTAMP:20260714T072934Z
SUMMARY:Control and Optimisation seminar – Sahani Pathiraja (University o
 f New South Wales)
DESCRIPTION:Title\nWasserstein Fisher Rao gradient flows: Sequential Monte 
 Carlo & Operator Splitting\nAbstract\nWasserstein-Fisher-Rao (WFR) gradien
 t flows have recently been proposed for sampling from a target probability
  distribution\, a task that is common across many areas of machine learnin
 g\, Bayesian statistics and statistical mechanics.  Such gradient flows 
 have been shown to accelerate convergence over pure Wasserstein Gradient f
 lows by combining the benefits of both diffusive-transport (Wasserstein) a
 nd reweighting (Fisher-Rao) type gradient flows.  We consider a Wasserst
 ein-Fisher-Rao flow for the Kullback-Leibler divergence and connect them t
 o well-known Monte Carlo algorithms.  In doing so\, we show that these l
 ead to a natural implementation using importance sampling and propose a se
 quential Monte Carlo based algorithm for solving a WFR gradient flow.  W
 e study the algorithm both empirically and theoretically.  Additional be
 nefits arising from operator splitting will also be discussed. \nBio\n\nS
 ahani Pathiraja is a Lecturer in the School of Mathematics and Statistics 
 at the University of New South Wales\, Sydney Australia.  Her research in
 terests span stochastic filtering\, sequential Bayesian inference\, McKean
 -Vlasov SDEs\, data assimilation and more recently\, sampling and gradient
  flows.\n
URL:https://www.imperial.ac.uk/events/199110/control-and-optimisation-semin
 ar-sahani-pathiraja-university-of-new-south-wales/
DTSTART;TZID=Europe/London:20251008T140000
DTEND;TZID=Europe/London:20251008T150000
LOCATION:410\, Huxley Building\, South Kensington Campus\, Imperial College
  London\, London\, SW7 2AZ\, United Kingdom
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