All lectures to be held in Meeting Room 1, Radcliffe House

Monday February 22nd

09:15-09:55 Dean Oliver Metropolized Randomized Maximum Likelihood for sampling from multimodal distributions pdf
10:00-10:40 Sebastian Reich Non-Gaussian data assimilation via a localized hybrid ensemble transform filter pdf
10:45-11:30 Coffee/Tea
11:30-12:10 Themis Sapsis Uncertainty quantification of complex systems through adaptive reduced order subspaces
12:15-12:55 Raul Tempone Multi-index Monte Carlo and Multi-index Stochastic Collocation pdf
13:00-14:15 Lunch
14:15-14:55 Simon Arridge Dynamic PhotoAcoustic Tomography
15:00-15:40 Raymond Chan Point-spread function reconstruction in ground-based astronomy
15:45-16:30 Coffee/Tea
16:30-17:10 Carola Schoenlieb Bilevel optimisation for variational regularisation models pdf
18:00-19:30 Dinner

Tuesday February 23rd

09:15-09:55 Tim Sullivan Probabilistic Numerics for Differential Equation
10:00-10:40 Dave Albers Data assimilation in biomedicine with a focus on glucose forecasting for type 2 diabetics
10:45-11:30 Coffee/Tea
11:30-12:10 Jan Mandel Data assimilation on random smooth functions with applications to ensemble Kalman filter and satellite fire detection pdf
12:15-12:55 Tapio Helin Large noise in variational regularization pdf
13:00-14:15 Lunch
14:15-14:55 Omar Ghattas Scalable algorithms for optimal experimental design for infinite dimensional nonlinear Bayesian inverse problems pdf
15:00-15:40 Omiros Papaspiliopoulos The intrinsic dimension of importance sampling
15:45-16:30 Coffee/Tea
16:30-17:10 Bjorn Sprungk Generalized pCN Metropolis algorithms for Bayesian inference in Hilbert spaces pdf
18:00-19:30 Dinner

Wednesday February 24th

09:15-09:55 Andrew Stuart Analysis of the ensemble Kalman filter for inverse problems
10:00-10:40 Sergios Agapiou Unbiased Estimation and Exact Simulation for Bayesian Inverse Problems
10:45-11:30 Coffee/Tea
11:30-12:10 Mike Christie Multilevel Hamiltonian Monte Carlo for Quantifying Uncertainty in Reservoir Simulation
12:15-12:55 Marco Iglesias A Bayesian level-set approach for geometric inverse problems
13:00-14:15 Lunch