research
∙
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...
share
research
∙
04/22/2022
Error-in-variables modelling for operator learning
Deep operator learning has emerged as a promising tool for reduced-order...
research
∙
12/09/2020
Thermodynamically consistent physics-informed neural networks for hyperbolic systems
Physics-informed neural network architectures have emerged as a powerful...
research
∙
05/21/2019