Jan Niklas Fuhg

33 papers Journal 33

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Monolithic Computational Homogenization Framework for Nearly Incompressible Magnetoelastic Composites. CoRR L. River Spencer, Manuel K. Rausch, Chad M. Landis, Jan Niklas Fuhg
2026	J	`jnl`	Differentiable neural network representation of multi-well, locally-convex potentials. J. Comput. Phys. Reese E. Jones, Adrian Buganza Tepole, Jan Niklas Fuhg
2025	J	`jnl`	A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM. CoRR Sanjeev Kumar, D. Thomas Seidl, Brian Neal Granzow, Jin Yang, Jan Niklas Fuhg
2025	J	`jnl`	Bubble Dynamics Transformer: Microrheology at Ultra-High Strain Rates. CoRR Lehu Bu, Zhaohan Yu, Shaoting Lin, Jan Niklas Fuhg, Jin Yang
2025	J	`jnl`	Deep Inverse Rosenblatt Transport for Structural Reliability Analysis. CoRR Aryan Tyagi, Jan Niklas Fuhg
2025	J	`jnl`	Differentiable neural network representation of multi-well, locally-convex potentials. CoRR Reese E. Jones, Adrian Buganza Tepole, Jan Niklas Fuhg
2025	J	`jnl`	Graph Neural Network Surrogates for Contacting Deformable Bodies with Necessary and Sufficient Contact Detection. CoRR Vijay K. Dubey, Collin E. Haese, Osman Gültekin, David Dalton, Manuel K. Rausch, Jan Niklas Fuhg
2025	J	`jnl`	Input Specific Neural Networks. CoRR Asghar A. Jadoon, D. Thomas Seidl, Reese E. Jones, Jan Niklas Fuhg
2025	J	`jnl`	Polyconvex Physics-Augmented Neural Network Constitutive Models in Principal Stretches. CoRR Adrian Buganza Tepole, Asghar A. Jadoon, Manuel K. Rausch, Jan Niklas Fuhg
2025	J	`jnl`	Thermodynamically Consistent Hybrid and Permutation-Invariant Neural Yield Functions for Anisotropic Plasticity. CoRR Asghar A. Jadoon, Ravi G. Patel, Brian Neal Granzow, Reese E. Jones, D. Thomas Seidl, Jan Niklas Fuhg
2024	J	`jnl`	A review on data-driven constitutive laws for solids. CoRR Jan Niklas Fuhg, Govinda Anantha Padmanabha, Nikolaos Bouklas, Bahador Bahmani, WaiChing Sun, Nikolaos N. Vlassis, Moritz Flaschel, Pietro Carrara, Laura De Lorenzis
2024	J	`jnl`	Automated model discovery of finite strain elastoplasticity from uniaxial experiments. CoRR Asghar A. Jadoon, Knut A. Meyer, Jan Niklas Fuhg
2024	J	`jnl`	Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models. CoRR Govinda Anantha Padmanabha, Jan Niklas Fuhg, Cosmin Safta, Reese E. Jones, Nikolaos Bouklas
2024	J	`jnl`	Inverse design of anisotropic microstructures using physics-augmented neural networks. CoRR Asghar A. Jadoon, Karl A. Kalina, Manuel K. Rausch, Reese E. Jones, Jan Niklas Fuhg
2024	J	`jnl`	Stress Representations for Tensor Basis Neural Networks: Alternative Formulations to Finger-Rivlin-Ericksen. J. Comput. Inf. Sci. Eng. Jan Niklas Fuhg, Nikolaos Bouklas, Reese E. Jones
2023	J	`jnl`	Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics. CoRR Jan Niklas Fuhg, Reese E. Jones, Nikolaos Bouklas
2023	J	`jnl`	NN-EVP: A physics informed neural network-based elasto-viscoplastic framework for predictions of grain size-aware flow response under large deformations. CoRR Adnan Eghtesad, Jan Niklas Fuhg, Nikolaos Bouklas
2023	J	`jnl`	Physics-informed Data-driven Discovery of Constitutive Models with Application to Strain-Rate-sensitive Soft Materials. CoRR Kshitiz Upadhyay, Jan Niklas Fuhg, Nikolaos Bouklas, K. T. Ramesh
2023	J	`jnl`	Stress representations for tensor basis neural networks: alternative formulations to Finger-Rivlin-Ericksen. CoRR Jan Niklas Fuhg, Nikolaos Bouklas, Reese E. Jones
2022	J	`jnl`	Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data. CoRR Jan Niklas Fuhg, Arnav Karmarkar, Teeratorn Kadeethum, Hongkyu Yoon, Nikolaos Bouklas
2022	J	`jnl`	Modular machine learning-based elastoplasticity: generalization in the context of limited data. CoRR Jan Niklas Fuhg, Craig M. Hamel, Kyle Johnson, Reese E. Jones, Nikolaos Bouklas
2022	J	`jnl`	The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity. J. Comput. Phys. Jan Niklas Fuhg, Nikolaos Bouklas
2021	J	`jnl`	A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. CoRR Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas
2021	J	`jnl`	A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. Nat. Comput. Sci. Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas
2021	J	`jnl`	Interval and fuzzy physics-informed neural networks for uncertain fields. CoRR Jan Niklas Fuhg, Amelie Fau, Nikolaos Bouklas
2021	J	`jnl`	Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks. CoRR Jan Niklas Fuhg, Michele Marino, Nikolaos Bouklas
2021	J	`jnl`	Model-data-driven constitutive responses: application to a multiscale computational framework. CoRR Jan Niklas Fuhg, Christoph Böhm, Nikolaos Bouklas, Amelie Fau, Peter Wriggers, Michele Marino
2021	J	`jnl`	On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling. CoRR Jan Niklas Fuhg, Nikolaos Bouklas
2021	J	`jnl`	The mixed deep energy method for resolving concentration features in finite strain hyperelasticity. CoRR Jan Niklas Fuhg, Nikolaos Bouklas
2020	J	`jnl`	A machine learning based plasticity model using proper orthogonal decomposition. CoRR Dengpeng Huang, Jan Niklas Fuhg, Christian Weißenfels, Peter Wriggers
2019	J	`jnl`	Adaptive surrogate models for parametric studies. CoRR Jan Niklas Fuhg
2019	J	`jnl`	An innovative adaptive kriging approach for efficient binary classification of mechanical problems. CoRR Jan Niklas Fuhg, Amelie Fau
2019	J	`jnl`	Surrogate model approach for investigating the stability of a friction-induced oscillator of Duffing's type. CoRR Jan Niklas Fuhg, Amelie Fau