Challenges and Advances in High Dimensional and High Complexity Monte Carlo Computation and Theory
Videos from BIRS Workshop
Roland Assaraf, Université Pierre et Marie Curie
Monday Mar 19, 2012 09:13 - 10:03
Correlated sampling without re-weighting: computing properties with size-independent variances
Michele Parrinello, Eidgenössische Technische Hochschule Zürich and Università della Svizzera Italiana, Lugano
Monday Mar 19, 2012 10:40 - 11:34
Sampling complex distributions in physics, chemistry and biology
David van Dyk, Imperial College London
Monday Mar 19, 2012 14:17 - 15:03
Computational challenges with complex data for complex astrophysics
Nando de Freitas, University of British Columbia
Tuesday Mar 20, 2012 09:51 - 10:33
Adaptive MCMC for high dimensional and high complexity problems
Jeffrey Rosenthal, University of Toronto
Tuesday Mar 20, 2012 11:03 - 11:49
Adapting Metropolis algorithms and Gibbs samplers
Christian Robert, Paris Dauphine University
Tuesday Mar 20, 2012 13:32 - 14:20
Approximate Bayesian Computation for model selection
Francois Perron, University of Montreal
Tuesday Mar 20, 2012 14:21 - 15:06
Bayesian estimation of copulas based on ranks and ABC
Scott Sisson, University of New South Wales
Tuesday Mar 20, 2012 15:31 - 16:15
Approximate Bayesian Computation in high dimensions
Zhiqiang Tan, Rutgers University
Tuesday Mar 20, 2012 16:16 - 17:07
A sampling algorithm via tempering, importance subsampling and Markov chain moving
Gareth 0. Roberts, University of Warwick
Wednesday Mar 21, 2012 09:01 - 09:49
Sequential importance sampling for irreducible diffusions
Jun Liu, Harvard University
Wednesday Mar 21, 2012 10:45 - 11:30
On two ideas in sequential Monte Carlo methods
Helene Massam, York University
Thursday Mar 22, 2012 09:05 - 09:50
Bayes factors and the geometry of discrete loglinear models
Faming Liang, Texas A&M University
Thursday Mar 22, 2012 09:51 - 10:36
Bayesian subset modeling for high dimensional generalized linear models and its asymptotic properties
James Hobert, University of Florida
Thursday Mar 22, 2012 11:09 - 11:44
Convergence rate results for two Gibbs samplers
Krzysztof Latuszynski, University of Warwick
Thursday Mar 22, 2012 13:32 - 14:12
Why does the Gibbs sampler work on hierarchical models?
Jose Blanchet, Stanford
Thursday Mar 22, 2012 15:30 - 16:16
Advances in efficient Monte Carlo for stochastic networks
