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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 · cs.LGShow all

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cs.LG2021★ 1 cited

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg +4

This work is the first to employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) towards learning a forward and an inve…