BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Национален център за високопроизводителни и разпределени пресмятания - ECPv4.9.5//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Национален център за високопроизводителни и разпределени пресмятания
X-ORIGINAL-URL:http://nchdc.acad.bg
X-WR-CALDESC:Events for Национален център за високопроизводителни и разпределени пресмятания
BEGIN:VTIMEZONE
TZID:"Europe/Sofia"
BEGIN:DAYLIGHT
TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20170326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20171029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20170703
DTEND;VALUE=DATE:20170708
DTSTAMP:20230923T132136
CREATED:20170612T120727Z
LAST-MODIFIED:20190610T002338Z
UID:733-1499040000-1499471999@nchdc.acad.bg
SUMMARY:International Conference on Monte Carlo Methods and Applications (MCM 2017)
DESCRIPTION:The biennial International Conference on Monte Carlo Methods and Applications (MCM) is a mathematically-oriented meeting devoted to the study of stochastic simulation and Monte Carlo methods in general\, from the theoretical viewpoint and in terms of their effective applications in different areas such as finance\, statistics\, machine learning\, computer graphics\, computational physics\, biology\, chemistry\, and scientific computing in general. \nConference topics include:\nMonte Carlo methods and principles; pseudorandom number generators; low-discrepancy point sets and sequences in various spaces; quasi-Monte Carlo and randomized quasi-Monte Carlo methods; simulation of random variates and random processes; variance reduction and efficiency improvement methods for simulation; rare-event simulation methods; multilevel Monte Carlo methods; stochastic optimization methods based on simulation and random search; simulation algorithms for highly-parallel computing environments; tractability and complexity analysis of multivariate problems (integration\, approximation\, etc.); Monte Carlo and quasi-Monte Carlo methods for stochastic differential equations and partial differential equations; Markov chain Monte Carlo particle filters\, splitting\, and other adaptive learning methods; Monte Carlo methods in machine learning; applications in physics\, chemistry\, biology\, economy\, finance\, statistics\, management\, medical science\, computer graphics\, etc. \n
URL:http://nchdc.acad.bg/event/international-conference-on-monte-carlo-methods-and-applicationsmcm-2017/
END:VEVENT
END:VCALENDAR