| Analyses of Internal Structures and Defects in Materials Using Physics-Informed Neural Networks E Zhang, M Dao, GE Karniadakis, S Suresh Science Advances 8 (7), eabk0644, 2022 | 240 | 2022 |
| Fatigue Fracture of Nearly Elastic Hydrogels E Zhang, R Bai, XP Morelle, Z Suo Soft Matter 14 (18), 3563-3571, 2018 | 140 | 2018 |
| Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging E Zhang, M Yin, G Karniadakis AAAI Fall 2020 Symposium on Physics-Guided AI to Accelerate Scientific Discovery, 2020 | 121 | 2020 |
| Interfacing Finite Elements with Deep Neural Operators for Fast Multiscale Modeling of Mechanics Problems M Yin, E Zhang, Y Yu, GE Karniadakis Computer Methods in Applied Mechanics and Engineering, 115027, 2022 | 96 | 2022 |
| Recent advances and applications of machine learning in experimental solid mechanics: A review H Jin, E Zhang, HD Espinosa Applied Mechanics Reviews 75 (6), 061001, 2023 | 70 | 2023 |
| Modeling finite-strain plasticity using physics-informed neural network and assessment of the network performance S Niu, E Zhang, Y Bazilevs, V Srivastava Journal of the Mechanics and Physics of Solids 172, 105177, 2023 | 67 | 2023 |
| Simulating Progressive Intramural Damage Leading to Aortic Dissection Using DeepONet: an Operator-Regression Neural Network M Yin, E Ban, BV Rego, E Zhang, C Cavinato, JD Humphrey, ... Journal of the Royal Society Interface 19 (187), 20210670, 2022 | 53 | 2022 |
| Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers E Zhang, A Kahana, A Kopaničáková, E Turkel, R Ranade, J Pathak, ... arXiv preprint arXiv:2208.13273, 2022 | 33 | 2022 |
| A Computational Model of Bio-Inspired Soft Network Materials for Analyzing Their Anisotropic Mechanical Properties E Zhang, Y Liu, Y Zhang Journal of Applied Mechanics 85 (7), 071002, 2018 | 20 | 2018 |
| On the geometry transferability of the hybrid iterative numerical solver for differential equations A Kahana, E Zhang, S Goswami, G Karniadakis, R Ranade, J Pathak Computational Mechanics 72 (3), 471-484, 2023 | 14 | 2023 |
| A generative modeling framework for inferring families of biomechanical constitutive laws in data-sparse regimes M Yin, Z Zou, E Zhang, C Cavinato, JD Humphrey, GE Karniadakis Journal of the Mechanics and Physics of Solids 181, 105424, 2023 | 11 | 2023 |
| G2Φnet: Relating genotype and biomechanical phenotype of tissues with deep learning E Zhang, B Spronck, JD Humphrey, GE Karniadakis PLOS Computational Biology 18 (10), e1010660, 2022 | 8 | 2022 |
| Mechanical characterization and inverse design of stochastic architected metamaterials using neural operators H Jin, E Zhang, B Zhang, S Krishnaswamy, GE Karniadakis, HD Espinosa arXiv preprint arXiv:2311.13812, 2023 | 7 | 2023 |
| Large scale scattering using fast solvers based on neural operators Z Zou, A Kahana, E Zhang, E Turkel, R Ranade, J Pathak, GE Karniadakis arXiv preprint arXiv:2405.12380, 2024 | 3 | 2024 |
| DDDAS for Systems Analytics in Applied Mechanics A Korobenko, S Niu, X Deng, E Zhang, V Srivastava, Y Bazilevs International Conference on Dynamic Data Driven Applications Systems, 353-361, 2022 | | 2022 |
