| Data-driven tissue mechanics with polyconvex neural ordinary differential equations V Tac, FS Costabal, AB Tepole Computer Methods in Applied Mechanics and Engineering 398, 115248, 2022 | 45 | 2022 |
| Data-driven modeling of the mechanical behavior of anisotropic soft biological tissue V Tac, VD Sree, MK Rausch, AB Tepole Engineering with Computers 38 (5), 4167–4182, 2022 | 37 | 2022 |
| Benchmarking physics-informed frameworks for data-driven hyperelasticity V Taç, K Linka, F Sahli-Costabal, E Kuhl, AB Tepole Computational Mechanics 73 (1), 49-65, 2024 | 25* | 2024 |
| Predicting the mechanical properties of biopolymer gels using neural networks trained on discrete fiber network data Y Leng, V Tac, S Calve, AB Tepole Computer Methods in Applied Mechanics and Engineering 387, 114160, 2021 | 20 | 2021 |
| Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations V Taç, MK Rausch, FS Costabal, AB Tepole Computer Methods in Applied Mechanics and Engineering 411, 116046, 2023 | 17 | 2023 |
| Micromechanical modelling of carbon nanotube reinforced composite materials with a functionally graded interphase V Taç, E Gürses Journal of Composite Materials 53 (28-30), 4337-4348, 2019 | 8 | 2019 |
| Experimental Determination of the Stress Intensity Factor Using Photoelasticity W Taj Matter 2 (1), 2110-2116, 2015 | 3 | 2015 |
| Dynamic frictional sliding modes between two homogenous interfaces W Taj, D Coker IOP Conference Series: Materials Science and Engineering 295 (1), 012001, 2018 | 1 | 2018 |
| Generative Hyperelasticity with Physics-Informed Probabilistic Diffusion Fields V Tac, MK Rausch, I Bilionis, FS Costabal, AB Tepole arXiv preprint arXiv:2310.03745, 2023 | | 2023 |
| Data-Driven Continuum Damage Mechanics with Built-In Physics V Tac, E Kuhl, A Buganza Tepole Available at SSRN 4791814, 0 | | |
Adrián Buganza TepolePurdue UniversityVerified email at purdue.edu
