4 citations · 11 across the 8 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2023
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides
Sharmila Karumuri, Ilias Bilionis
Inverse problems, i.e., estimating parameters of physical models from experimental data, are ubiquitous in science and engineering. The Bayesian formulation is the gold standard be…
stat.ML2019
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis +1
Estimating arbitrary quantities of interest (QoIs) that are non-linear operators of complex, expensive-to-evaluate, black-box functions is a challenging problem due to missing doma…