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SUMMARY:Sampling of Integrand for Integral Calculation Using Shallow Neura
l Network
DTSTART;VALUE=DATE-TIME:20220708T081500Z
DTEND;VALUE=DATE-TIME:20220708T090000Z
DTSTAMP;VALUE=DATE-TIME:20221207T074452Z
UID:indico-contribution-17007@indico.jinr.ru
DESCRIPTION:Speakers: Vladimir Papoyan (JINR)\nWe present the effect of us
ing the Metropolis-Hastings algorithm for sampling the integrand on the ac
curacy of calculating the value of the integral. In addition\, a hybrid me
thod for sampling the integrand is proposed\, in which part of the trainin
g sample is generated by applying the Metropolis-Hastings algorithm\, and
the other part includes points of a uniform grid. Numerical experiments sh
ow that when integrating in high-dimensional domains\, sampling of integra
nds both by the Metropolis-Hastings algorithm and by a hybrid method is mo
re efficient with respect to the points of a uniform grid.\n\nhttps://indi
co.jinr.ru/event/3084/contributions/17007/
LOCATION:
URL:https://indico.jinr.ru/event/3084/contributions/17007/
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