| A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method S Rezaei, A Harandi, A Moeineddin, BX Xu, S Reese Computer Methods in Applied Mechanics and Engineering 401, 115616, 2022 | 127 | 2022 |
| Mixed formulation of physics‐informed neural networks for thermo‐mechanically coupled systems and heterogeneous domains A Harandi, A Moeineddin, M Kaliske, S Reese, S Rezaei International Journal for Numerical Methods in Engineering 125 (4), e7388, 2024 | 41 | 2024 |
| Learning solutions of thermodynamics-based nonlinear constitutive material models using physics-informed neural networks S Rezaei, A Moeineddin, A Harandi Computational Mechanics 74 (2), 333-366, 2024 | 19 | 2024 |
| Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations S Rezaei, A Moeineddin, M Kaliske, M Apel arXiv preprint arXiv:2401.02363, 2024 | 6 | 2024 |
| Physics-informed neural networks applied to catastrophic creeping landslides A Moeineddin, C Seguí, S Dueber, R Fuentes Landslides 20 (9), 1853-1863, 2023 | 5 | 2023 |
| Finite operator learning: Bridging neural operators and numerical methods for efficient parametric solution and optimization of pdes S Rezaei, RN Asl, K Taghikhani, A Moeineddin, M Kaliske, M Apel arXiv preprint arXiv:2407.04157, 2024 | 3 | 2024 |
| Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN S Rezaei, A Moeineddin, A Harandi arXiv preprint arXiv:2304.06044, 2023 | 3 | 2023 |
| Numerical investigations on rubber-snow interaction utilizing an elastoplastic snow model with implicit gradient damage enhancement A Moeineddin, J Platen, M Kaliske Constitutive Models for Rubbers XIII, 54-59, 2025 | | 2025 |
| Constitutive description of snow at finite strains by the modified cam‐clay model and an implicit gradient damage formulation A Moeineddin, J Platen, M Kaliske International Journal for Numerical Methods in Engineering 125 (24), e7595, 2024 | | 2024 |
| Phase-field fracture model solved by a mixed formulation for physics-informed neural networks A Harandi, S Rezaei, A Moeineddin, T Brepols, S Reese | | |
