| Physics-informed learning of governing equations from scarce data Z Chen, Y Liu, H Sun Nature Communications 12, 6136, 2021 | 417 | 2021 |
| Physics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling R Zhang, Y Liu, H Sun Engineering Structures 215, 110704, 2020 | 374 | 2020 |
| Physics-Informed Multi-LSTM Networks for Metamodeling of Nonlinear Structures R Zhang, Y Liu, H Sun Computer Methods in Applied Mechanics and Engineering 369, 113226, 2020 | 364 | 2020 |
| Physics-Informed Deep Learning for Computational Elastodynamics without Labeled Data C Rao, H Sun, Y Liu Journal of Engineering Mechanics 147 (8), 04021043, 2021 | 295 | 2021 |
| Physics-informed deep learning for incompressible laminar flows C Rao, H Sun, Y Liu Theoretical and Applied Mechanics Letters 10 (3), 207-212, 2020 | 293 | 2020 |
| Three-dimensional convolutional neural network (3D-CNN) for heterogeneous material homogenization C Rao, Y Liu Computational Materials Science 184, 109850, 2020 | 262 | 2020 |
| PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs P Ren, C Rao, Y Liu, J Wang, H Sun Computer Methods in Applied Mechanics and Engineering 389, 114399, 2022 | 202 | 2022 |
| A nonlocal multiscale discrete‐continuum model for predicting mechanical behavior of granular materials Y Liu, WC Sun, Z Yuan, J Fish International Journal for Numerical Methods in Engineering 106 (2), 129-160, 2016 | 116 | 2016 |
| Transient dynamic behavior of polypropylene fiber reinforced mortar under compressive impact loading H Zhang, Y Liu, H Sun, S Wu Construction and Building Materials 111, 30-42, 2016 | 93 | 2016 |
| Statistical regularization for identification of structural parameters and external loadings using state space models H Sun, D Feng, Y Liu, MQ Feng Computer‐Aided Civil and Infrastructure Engineering 30 (11), 843-858, 2015 | 91 | 2015 |
| Encoding physics to learn reaction–diffusion processes C Rao, P Ren, Q Wang, O Buyukozturk, H Sun, Y Liu Nature Machine Intelligence 5 (7), 765-779, 2023 | 90 | 2023 |
| Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search F Sun, Y Liu, JX Wang, H Sun The Eleventh International Conference on Learning Representations (ICLR), 2023 | 60 | 2023 |
| Determining Material Parameters for Critical State Plasticity Models Based On Multilevel Extended Digital Database Y Liu, WC Sun, J Fish Journal of Applied Mechanics 83 (1), 011003, 2016 | 57 | 2016 |
| Automated modeling of random inclusion composites M Bailakanavar, Y Liu, J Fish, Y Zheng Engineering with Computers 30 (4), 609-625, 2014 | 57 | 2014 |
| A regularized phenomenological multiscale damage model Y Liu, V Filonova, N Hu, Z Yuan, J Fish, Z Yuan, T Belytschko International Journal for Numerical Methods in Engineering 99 (12), 867-887, 2014 | 54 | 2014 |
| SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain P Ren, C Rao, S Chen, JX Wang, H Sun, Y Liu Computer Physics Communications 295, 109010, 2024 | 44 | 2024 |
| PhySR: Physics-informed deep super-resolution for spatiotemporal data P Ren, C Rao, Y Liu, Z Ma, Q Wang, JX Wang, H Sun Journal of Computational Physics 492, 112438, 2023 | 39 | 2023 |
| Mesoscale computational modeling of concrete-like particle-reinforced composites with non-convex aggregates QX Meng, D Lv, Y Liu Computers & Structures 240, 106349, 2020 | 39 | 2020 |
| Physics-informed Spline Learning for Nonlinear Dynamics Discovery F Sun, Y Liu, H Sun Proceedings of the 30th International Joint Conference on Artificial …, 2021 | 35 | 2021 |
| Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning C Rao, P Ren, Y Liu, H Sun The Tenth International Conference on Learning Representations (ICLR), 1-19, 2022 | 33 | 2022 |
