79 citations · 105 across the 7 of their papers we have counts for
3 papers · 1 filter
Multilevel Double Loop Monte Carlo and Stochastic Collocation Methods with Importance Sampling for Bayesian Optimal Experimental Design
Joakim Beck, Ben Mansour Dia, Luis F. R. Espath +1
An optimal experimental set-up maximizes the value of data for statistical inferences and predictions. The efficiency of strategies for finding optimal experimental set-ups is part…
Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under Uncertainty
Marco Ballesio, Joakim Beck, Anamika Pandey +3
We interpret uncertainty in a model for seismic wave propagation by treating the model parameters as random variables, and apply the Multilevel Monte Carlo (MLMC) method to reduce…
IGA-based Multi-Index Stochastic Collocation for random PDEs on arbitrary domains
Joakim Beck, Lorenzo Tamellini, Raúl Tempone
This paper proposes an extension of the Multi-Index Stochastic Collocation (MISC) method for forward uncertainty quantification (UQ) problems in computational domains of shape othe…