UQ14 - MS26-1 - Dimension-independent Likelihood-informed MCMC Samplers Presentation: Tiangang Cui, Massachusetts Institute of Technology, USA, 27 min 17 sec
UQ14 - MS26-2 - Surrogate Geometry for Geodesic MCMC Presentation: Mark Girolami, University College London, United Kingdom, 29 min 30 sec
UQ14 - MS26-3 - Structure-Exploiting Sampling Methods for Large Scale Bayesian Inverse Problems in High Dimensional Parameter Spaces Presentation: Tan Bui-Thanh, University of Texas at Austin, USA, 26 min 27 sec
UQ14 - MS26-3 - Structure-Exploiting Sampling Methods for Large Scale Bayesian Inverse Problems in High Dimensional Parameter Spaces (PDF) Link: View PDF Handout
UQ14 - MS26-4 - Exploiting Geometry in MCMC Using Optimal Transport Theory Presentation: Matthew Parno, Massachusetts Institute of Technology, USA, 20 min 59 sec