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20212026
most citedOn physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling

130 citations · 549 across the 28 of their papers we have counts for

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Showing 2021 · math.NAShow all

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math.NA2021

Interval and fuzzy physics-informed neural networks for uncertain fields

Jan Niklas Fuhg, Ioannis Kalogeris, Amélie Fau +1

Temporally and spatially dependent uncertain parameters are regularly encountered in engineering applications. Commonly these uncertainties are accounted for using random fields an…

math.NA2021★ 19 cited

Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation

T. Kadeethum, F. Ballarin, N. Bouklas

We present a non-intrusive model reduction framework for linear poroelasticity problems in heterogeneous porous media using proper orthogonal decomposition (POD) and neural network…