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SUMMARY:Computational mathematics for model reduction and predictive model
 ling in molecular and complex systems
DTSTART:20190521T080000
DTEND:20190529T180000
DTSTAMP:20260508T164316Z
UID:19ece32e4482b874d7d3760f11257786ceac90dc088a69afdeb987e6
CATEGORIES:Conferences - Seminars
DESCRIPTION:Markos Katsoulakis\, University of Massachusetts Amherst Bene
 dikt Leimkuhler\, University of Edinburgh Petr Pelchac\, University of D
 elaware Anders Szepessy\, KTH Royal Institute of Technology\nThe workshop
  will address computational and theoretical issues in stochastic modeling 
 and model reduction in molecular and complex systems. In particular\, the 
 program will include topics ranging from quantum to mesoscale modelling\, 
 with focus on uncertainty quantification\, machine learning and approximat
 e inference method\, methods using both quantum and classical models\, sem
 iclassical limits and their computational aspect. Furthermore\, the interp
 lay between mathematical analysis\, modeling and statistical physics and t
 rade-offs between statistical (data-driven) learning and physicochemical m
 odelling will be part of the discussions. The workshop aims at bringing to
 gether mathematicians and domain scientists interested in applications suc
 h as systems with excited states\, empirical potentials\, kinetic Monte Ca
 rlo methods and accelerated simulation methods determined from molecular d
 ynamics\, data assimilation and inference for predictive modeling of compl
 ex molecular systems.\n\nPart of the Semester : Multi-scale Mathematical 
 Modelling and Coarse-grain Computational Chemistry
LOCATION:GA 3 21 https://plan.epfl.ch/?room=GA321
STATUS:CONFIRMED
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