Jan N. Fuhg

State-of-the-Art and Comparative Review of Adaptive Sampling Methods for Kriging

Jan N. Fuhg, Amélie Fau, Udo Nackenhorst · Archives of Computational Methods in Engineering · 2020 · 254 citations · Full text

A machine learning based plasticity model using proper orthogonal decomposition

Dengpeng Huang, Jan N. Fuhg, Christian Weißenfels et al. · Computer Methods in Applied Mechanics and Engineering · 2020 · 171 citations · Full text

Engineering, Machine Learning, Pattern Recognition +5

The mixed deep energy method for resolving concentration features in\n finite strain hyperelasticity

Jan N. Fuhg, Nikolaos Bouklas · arXiv (Cornell University) · 2021 · 131 citations · Full text

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

Jan N. Fuhg, Nikolaos Bouklas · Computer Methods in Applied Mechanics and Engineering · 2022 · 108 citations · Full text

Engineering, Machine Learning, Probabilistic Machine Learning +17

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

Teeratorn Kadeethum, Daniel O’Malley, Jan N. Fuhg et al. · Nature Computational Science · 2021 · 81 citations · Full text

Artificial Intelligence, Parameter Estimation, Engineering +11