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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Bayesian Quadrature for Multiple Related Integrals
- Francois-Xavier Briol (Imperial College London\
; University of Warwick\; University of Oxford)
DTSTART;TZID=Europe/London:20180221T110000
DTEND;TZID=Europe/London:20180221T130000
UID:TALK101254AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/101254
DESCRIPTION:Bayesian probabilistic numerical methods are a set
of tools providing posterior distributions on the
output of numerical methods. The use of these met
hods is usually motivated by the fact that they ca
n represent our uncertainty due to incomplete/fini
te information about the continuous mathematical p
roblem being approximated. In this talk\, we demon
strate that this paradigm can provide additional a
dvantages\, such as the possibility of transferrin
g information between several numerical methods. T
his allows users to represent uncertainty in a mor
e faithfully manner and\, as a by-product\, provid
e increased numerical efficiency. We propose the f
irst such numerical method by extending the well-k
nown Bayesian quadrature algorithm to the case whe
re we are interested in computing the integral of
several related functions. We then demonstrate its
efficiency in the context of multi-fidelity model
s for complex engineering systems\, as well as a p
roblem of global illumination in computer graphics
.

LOCATION:Seminar Room 2\, Newton Institute
CONTACT:INI IT
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