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02/11/2019
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime
The automated construction of coarse-grained models represents a pivotal...
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06/21/2018
A data-driven model order reduction approach for Stokes flow through random porous media
Direct numerical simulation of Stokes flow through an impermeable, rigid...
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11/07/2017
Bayesian model and dimension reduction for uncertainty propagation: applications in random media
Well-established methods for the solution of stochastic partial differen...
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03/06/2017