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DTSTART:19700329T010000
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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Consensus-based sampling - Urbain Vaes (INRIA\, EN
PC - Ă‰cole des Ponts ParisTech\, INRIA Paris - Roc
quencourt)
DTSTART;TZID=Europe/London:20220429T121500
DTEND;TZID=Europe/London:20220429T131500
UID:TALK171905AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/171905
DESCRIPTION:In the first part of this talk\, I will present ba
ckground material on Bayesian inverse problems\, t
he associated challenges at the numerical level\,
and gradient-free sampling and optimization approa
ches for solving them. \; In the second part\,
I will present recent work [1] on a novel gradien
t-free sampling method that is well suited for Bay
esian inverse problems. The method is inspired by
consensus-based methods in optimization and based
on a stochastic interacting particle system. We de
monstrate its potential in regimes where the targe
t distribution is unimodal and close to Gaussian\;
indeed we prove that it enables to recover a Lapl
ace approximation of the measure in certain parame
tric regimes and provide numerical evidence that t
his Laplace approximation attracts a large set of
initial conditions in a number of examples.\n
\; \; \; [1] https://arxiv.org/abs/2106.02
519
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:
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