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09/11/2023
Interpretable learning of effective dynamics for multiscale systems
The modeling and simulation of high-dimensional multiscale systems is a ...
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03/03/2023
Interpretable reduced-order modeling with time-scale separation
Partial Differential Equations (PDEs) with high dimensionality are commo...
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09/06/2022
Semi-supervised Invertible DeepONets for Bayesian Inverse Problems
Deep Operator Networks (DeepONets) offer a powerful, data-driven tool fo...
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11/19/2021
Physics-enhanced Neural Networks in the Small Data Regime
Identifying the dynamics of physical systems requires a machine learning...
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02/08/2021
Physics-aware, deep probabilistic modeling of multiscale dynamics in the Small Data regime
The data-based discovery of effective, coarse-grained (CG) models of hig...
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01/14/2021
Physics-aware, probabilistic model order reduction with guaranteed stability
Given (small amounts of) time-series' data from a high-dimensional, fine...
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12/30/2019
