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SUMMARY:Introduction to Stochastic Modeling and MCMC methods - Christian S
 oize (Université Gustave Eiffel)
DTSTART:20230710T101500Z
DTEND:20230710T111500Z
UID:TALK193879@talks.cam.ac.uk
DESCRIPTION:Lecture: Monday 10 July 2023\, 11:15 &ndash\; 12:15Title: Intr
 oduction to stochastic modeling and MCMC methodsPresenter: Christian SOIZE
 \n1. Introduction to stochastic modeling in Uncertainty Quantification (UQ
 ).- Aleatory and epistemic uncertainties.- Sources of uncertainties and va
 riabilities.- Major challenges for the computational models.- Brief summar
 y of a strategy in UQ.\n2. Multivariate Kernel Density Estimation (KDE) me
 thod in nonparametric statistics.- Problem definition.- Multivariate kerne
 l density estimation method.\n3. MCMC methods for generating realizations/
 samples.- Main algorithms for the MCMC method: Metropolis-Hastings\, Gibbs
  sampler\,&nbsp\;&nbsp\; Langevin Metropolis-Hastings\, MCMC Hamiltonian d
 ynamics algorithms.- Metropolis-Hastings algorithm.- Example and analysis 
 for the Metropolis-Hastings algorithm.- MCMC dissipative Hamiltonian dynam
 ics algorithm.- Example and analysis of the ISDE-based algorithm.
LOCATION:Seminar Room 1\, Newton Institute
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