485 citations · 878 across the 26 of their papers we have counts for
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physics.data-an2023
An information field theory approach to Bayesian state and parameter estimation in dynamical systems
Kairui Hao, Ilias Bilionis
Dynamical system state estimation and parameter calibration problems are ubiquitous across science and engineering. Bayesian approaches to the problem are the gold standard as they…
stat.ML2023★ 6 cited
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.ML2023★ 18 cited
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification
Alex Alberts, Ilias Bilionis
Data-driven approaches coupled with physical knowledge are powerful techniques to model systems. The goal of such models is to efficiently solve for the underlying field by combini…