Differentiable neural network representation of multi-well, locally-convex potentials.

Jan Niklas Fuhg https://orcid.org/0000-0002-5986-3770

Reese E. Jones Adrian Buganza Tepole Jan Niklas Fuhg Differentiable neural network representation of multi-well, locally-convex potentials. 2026 114688 551 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2026.114688 db/journals/jcphy/jcphy551.html#JonesTF26 streams/journals/jcphy

L. River Spencer Manuel K. Rausch Chad M. Landis Jan Niklas Fuhg A Monolithic Computational Homogenization Framework for Nearly Incompressible Magnetoelastic Composites. 2026 March abs/2603.25965 CoRR https://doi.org/10.48550/arXiv.2603.25965 db/journals/corr/corr2603.html#abs-2603-25965 streams/journals/corr

Asghar A. Jadoon D. Thomas Seidl Reese E. Jones Jan Niklas Fuhg Input Specific Neural Networks. 2025 March abs/2503.00268 CoRR https://doi.org/10.48550/arXiv.2503.00268 db/journals/corr/corr2503.html#abs-2503-00268 streams/journals/corr

Adrian Buganza Tepole Asghar A. Jadoon Manuel K. Rausch Jan Niklas Fuhg Polyconvex Physics-Augmented Neural Network Constitutive Models in Principal Stretches. 2025 March abs/2503.00575 CoRR https://doi.org/10.48550/arXiv.2503.00575 db/journals/corr/corr2503.html#abs-2503-00575 streams/journals/corr

Sanjeev Kumar D. Thomas Seidl Brian Neal Granzow Jin Yang Jan Niklas Fuhg A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM. 2025 March abs/2503.19782 CoRR https://doi.org/10.48550/arXiv.2503.19782 db/journals/corr/corr2503.html#abs-2503-19782 streams/journals/corr

Lehu Bu Zhaohan Yu Shaoting Lin Jan Niklas Fuhg Jin Yang Bubble Dynamics Transformer: Microrheology at Ultra-High Strain Rates. 2025 June abs/2506.11936 CoRR https://doi.org/10.48550/arXiv.2506.11936 db/journals/corr/corr2506.html#abs-2506-11936 streams/journals/corr

Reese E. Jones Adrian Buganza Tepole Jan Niklas Fuhg Differentiable neural network representation of multi-well, locally-convex potentials. 2025 June abs/2506.17242 CoRR https://doi.org/10.48550/arXiv.2506.17242 db/journals/corr/corr2506.html#abs-2506-17242 streams/journals/corr

Vijay K. Dubey Collin E. Haese Osman Gültekin David Dalton Manuel K. Rausch Jan Niklas Fuhg Graph Neural Network Surrogates for Contacting Deformable Bodies with Necessary and Sufficient Contact Detection. 2025 July abs/2507.13459 CoRR https://doi.org/10.48550/arXiv.2507.13459 db/journals/corr/corr2507.html#abs-2507-13459 streams/journals/corr

Asghar A. Jadoon Ravi G. Patel Brian Neal Granzow Reese E. Jones D. Thomas Seidl Jan Niklas Fuhg Thermodynamically Consistent Hybrid and Permutation-Invariant Neural Yield Functions for Anisotropic Plasticity. 2025 August abs/2508.15923 CoRR https://doi.org/10.48550/arXiv.2508.15923 db/journals/corr/corr2508.html#abs-2508-15923 streams/journals/corr

Aryan Tyagi Jan Niklas Fuhg Deep Inverse Rosenblatt Transport for Structural Reliability Analysis. 2025 September abs/2509.05061 CoRR https://doi.org/10.48550/arXiv.2509.05061 db/journals/corr/corr2509.html#abs-2509-05061 streams/journals/corr

Jan Niklas Fuhg Nikolaos Bouklas Reese E. Jones Stress Representations for Tensor Basis Neural Networks: Alternative Formulations to Finger-Rivlin-Ericksen. 2024 24 J. Comput. Inf. Sci. Eng. 9 https://doi.org/10.1115/1.4064650 db/journals/jcise/jcise24.html#FuhgBJ24 streams/journals/jcise

Jan Niklas Fuhg Govinda Anantha Padmanabha Nikolaos Bouklas Bahador Bahmani WaiChing Sun Nikolaos N. Vlassis Moritz Flaschel Pietro Carrara Laura De Lorenzis A review on data-driven constitutive laws for solids. 2024 abs/2405.03658 CoRR https://doi.org/10.48550/arXiv.2405.03658 db/journals/corr/corr2405.html#abs-2405-03658

Govinda Anantha Padmanabha Jan Niklas Fuhg Cosmin Safta Reese E. Jones Nikolaos Bouklas Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models. 2024 abs/2407.00761 CoRR https://doi.org/10.48550/arXiv.2407.00761 db/journals/corr/corr2407.html#abs-2407-00761 streams/journals/corr

Asghar A. Jadoon Knut A. Meyer Jan Niklas Fuhg Automated model discovery of finite strain elastoplasticity from uniaxial experiments. 2024 abs/2408.14615 CoRR https://doi.org/10.48550/arXiv.2408.14615 db/journals/corr/corr2408.html#abs-2408-14615 streams/journals/corr

Asghar A. Jadoon Karl A. Kalina Manuel K. Rausch Reese E. Jones Jan Niklas Fuhg Inverse design of anisotropic microstructures using physics-augmented neural networks. 2024 abs/2412.13370 CoRR https://doi.org/10.48550/arXiv.2412.13370 db/journals/corr/corr2412.html#abs-2412-13370 streams/journals/corr

Kshitiz Upadhyay Jan Niklas Fuhg Nikolaos Bouklas K. T. Ramesh Physics-informed Data-driven Discovery of Constitutive Models with Application to Strain-Rate-sensitive Soft Materials. 2023 abs/2304.13897 CoRR https://doi.org/10.48550/arXiv.2304.13897 db/journals/corr/corr2304.html#abs-2304-13897

Adnan Eghtesad Jan Niklas Fuhg Nikolaos Bouklas NN-EVP: A physics informed neural network-based elasto-viscoplastic framework for predictions of grain size-aware flow response under large deformations. 2023 abs/2307.04301 CoRR https://doi.org/10.48550/arXiv.2307.04301 db/journals/corr/corr2307.html#abs-2307-04301

Jan Niklas Fuhg Nikolaos Bouklas Reese E. Jones Stress representations for tensor basis neural networks: alternative formulations to Finger-Rivlin-Ericksen. 2023 abs/2308.11080 CoRR https://doi.org/10.48550/arXiv.2308.11080 db/journals/corr/corr2308.html#abs-2308-11080

Jan Niklas Fuhg Reese E. Jones Nikolaos Bouklas Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics. 2023 abs/2310.03652 CoRR https://doi.org/10.48550/arXiv.2310.03652 db/journals/corr/corr2310.html#abs-2310-03652

Jan Niklas Fuhg Nikolaos Bouklas The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity. 110839 2022 451 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2021.110839 db/journals/jcphy/jcphy451.html#FuhgB22

Jan Niklas Fuhg Arnav Karmarkar Teeratorn Kadeethum Hongkyu Yoon Nikolaos Bouklas Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data. 2022 abs/2206.04675 CoRR https://doi.org/10.48550/arXiv.2206.04675 db/journals/corr/corr2206.html#abs-2206-04675

Jan Niklas Fuhg Craig M. Hamel Kyle Johnson Reese E. Jones Nikolaos Bouklas Modular machine learning-based elastoplasticity: generalization in the context of limited data. 2022 abs/2210.08343 CoRR https://doi.org/10.48550/arXiv.2210.08343 db/journals/corr/corr2210.html#abs-2210-08343

Teeratorn Kadeethum Daniel O'Malley Jan Niklas Fuhg Youngsoo Choi Jonghyun Lee 0005 Hari S. Viswanathan Nikolaos Bouklas A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. 819-829 2021 1 Nat. Comput. Sci. 12 https://doi.org/10.1038/s43588-021-00171-3 https://www.wikidata.org/entity/Q114107326 db/journals/ncs/ncs1.html#KadeethumOFCLVB21

Jan Niklas Fuhg Christoph Böhm 0005 Nikolaos Bouklas Amelie Fau Peter Wriggers Michele Marino Model-data-driven constitutive responses: application to a multiscale computational framework. 2021 abs/2104.02650 CoRR https://arxiv.org/abs/2104.02650 db/journals/corr/corr2104.html#abs-2104-02650

Jan Niklas Fuhg Nikolaos Bouklas The mixed deep energy method for resolving concentration features in finite strain hyperelasticity. 2021 abs/2104.09623 CoRR https://arxiv.org/abs/2104.09623 db/journals/corr/corr2104.html#abs-2104-09623

Jan Niklas Fuhg Michele Marino Nikolaos Bouklas Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks. 2021 abs/2105.04554 CoRR https://arxiv.org/abs/2105.04554 db/journals/corr/corr2105.html#abs-2105-04554

Teeratorn Kadeethum Daniel O'Malley Jan Niklas Fuhg Youngsoo Choi Jonghyun Lee 0005 Hari S. Viswanathan Nikolaos Bouklas A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. 2021 abs/2105.13136 CoRR https://arxiv.org/abs/2105.13136 db/journals/corr/corr2105.html#abs-2105-13136

Jan Niklas Fuhg Amelie Fau Nikolaos Bouklas Interval and fuzzy physics-informed neural networks for uncertain fields. 2021 abs/2106.13727 CoRR https://arxiv.org/abs/2106.13727 db/journals/corr/corr2106.html#abs-2106-13727

Jan Niklas Fuhg Nikolaos Bouklas On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling. 2021 abs/2109.11028 CoRR https://arxiv.org/abs/2109.11028 db/journals/corr/corr2109.html#abs-2109-11028

Dengpeng Huang Jan Niklas Fuhg Christian Weißenfels Peter Wriggers A machine learning based plasticity model using proper orthogonal decomposition. 2020 abs/2001.03438 CoRR https://arxiv.org/abs/2001.03438 db/journals/corr/corr2001.html#abs-2001-03438

Jan Niklas Fuhg Adaptive surrogate models for parametric studies. 2019 abs/1905.05345 CoRR http://arxiv.org/abs/1905.05345 db/journals/corr/corr1905.html#abs-1905-05345

Jan Niklas Fuhg Amelie Fau An innovative adaptive kriging approach for efficient binary classification of mechanical problems. 2019 abs/1907.01490 CoRR http://arxiv.org/abs/1907.01490 db/journals/corr/corr1907.html#abs-1907-01490

Jan Niklas Fuhg Amelie Fau Surrogate model approach for investigating the stability of a friction-induced oscillator of Duffing's type. 2019 abs/1907.02208 CoRR http://arxiv.org/abs/1907.02208 db/journals/corr/corr1907.html#abs-1907-02208

Bahador Bahmani Christoph Böhm 0005 Nikolaos Bouklas Lehu Bu Pietro Carrara Youngsoo Choi David Dalton Vijay K. Dubey Adnan Eghtesad Amelie Fau Moritz Flaschel Brian GranzowBrian Neal Granzow Osman Gültekin Collin E. Haese Craig M. Hamel Dengpeng Huang Asghar A. Jadoon Kyle Johnson Reese E. Jones Teeratorn Kadeethum Karl A. Kalina Arnav Karmarkar Sanjeev Kumar Chad M. Landis Jonghyun Lee 0005 Shaoting Lin Laura De Lorenzis Michele Marino Knut A. Meyer Daniel O'Malley Govinda Anantha Padmanabha Ravi G. Patel K. T. Ramesh Manuel K. Rausch Cosmin Safta Daniel Thomas SeidlD. Thomas Seidl L. River Spencer WaiChing Sun Adrian Buganza Tepole Aryan Tyagi Kshitiz Upadhyay Hari S. Viswanathan Nikolaos VlassisNikolaos N. Vlassis Christian Weißenfels Peter Wriggers Jin Yang Hongkyu Yoon Zhaohan Yu