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20172026
most citedPhysics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport

396 citations · 673 across the 27 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

cs.LG2021★ 29 cited

Physics-Informed Machine Learning Method for Large-Scale Data Assimilation Problems

Yu-Hong Yeung, David A. Barajas-Solano, Alexandre M. Tartakovsky

We develop a physics-informed machine learning approach for large-scale data assimilation and parameter estimation and apply it for estimating transmissivity and hydraulic head in…

math.DS2021

Sparsifying Priors for Bayesian Uncertainty Quantification in Model Discovery

Seth M. Hirsh, David A. Barajas-Solano, J. Nathan Kutz

We propose a probabilistic model discovery method for identifying ordinary differential equations (ODEs) governing the dynamics of observed multivariate data. Our method is based o…