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03/20/2023
Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data
In complex large-scale systems such as climate, important effects are ca...
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04/22/2022
Error-in-variables modelling for operator learning
Deep operator learning has emerged as a promising tool for reduced-order...
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12/09/2020
Thermodynamically consistent physics-informed neural networks for hyperbolic systems
Physics-informed neural network architectures have emerged as a powerful...
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05/21/2019
