| NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations X Jin, S Cai, H Li, GE Karniadakis Journal of Computational Physics 426, 109951, 2021 | 1062 | 2021 |
| Prediction model of velocity field around circular cylinder over various Reynolds numbers by fusion convolutional neural networks based on pressure on the cylinder X Jin, P Cheng, WL Chen, H Li Physics of Fluids 30 (4), 2018 | 340 | 2018 |
| Time‑resolved reconstruction of flow field around a circular cylinder by recurrent neural networks based on non‑time‑resolved particle image velocimetry measurements X Jin, S Laima, WL Chen, H Li Experiments in Fluids 61, 114, 2020 | 60 | 2020 |
| A novel long short-term memory neural-network-based self-excited force model of limit cycle oscillations of nonlinear flutter for various aerodynamic configurations W Li, S Laima, X Jin, W Yuan, H Li Nonlinear Dynamics 100 (3), 2071-2087, 2020 | 57 | 2020 |
| General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning S Wei, X Jin, H Li Computational Mechanics 64 (5), 1361-1374, 2019 | 54* | 2019 |
| 物理增强的流场深度学习建模与模拟方法 金晓威， 赖马树金， 李惠 力学学报 53 (10), 2616-2629, 2021 | 24* | 2021 |
| Intelligent modeling of nonlinear dynamical systems by machine learning R Chen, X Jin, S Laima, Y Huang, H Li International Journal of Non-Linear Mechanics 142, 103984, 2022 | 20 | 2022 |
| Damage identification of long-span bridges based on the correlation of probability distribution of monitored quasi-static responses F Deng, S Wei, X Jin, Z Chen, H Li Mechanical Systems and Signal Processing 186, 109908, 2023 | 19 | 2023 |
| DeepTRNet: Time-resolved reconstruction of flow around a circular cylinder via spatiotemporal deep neural networks S Laima, X Zhou, X Jin, D Gao, H Li Physics of Fluids 35 (1), 2023 | 15 | 2023 |
| A machine learning based solver for pressure Poisson equations R Chen, X Jin, H Li Theoretical and Applied Mechanics Letters 12 (5), 100362, 2022 | 15 | 2022 |
| Cascade-Net for predicting cylinder wake at Reynolds numbers ranging from subcritical to supercritical regime J Mi, X Jin, H Li Physics of Fluids 35 (7), 2023 | 10 | 2023 |
| Deep learning reconstruction of high-Reynolds-number turbulent flow field around a cylinder based on limited sensors R Li, B Song, Y Chen, X Jin, D Zhou, Z Han, WL Chen, Y Cao Ocean Engineering 304, 117857, 2024 | 9 | 2024 |
| 土木工程智能科学与技术研究现状及展望 徐阳， 金晓威， 李惠 建筑结构学报 43 (9), 23, 2022 | 8 | 2022 |
| Machine learning modeling for the near-wake mean velocity deficit profiles behind a rough circular cylinder J Mi, S Laima, X Jin, H Li Ocean Engineering 259, 111791, 2022 | 7 | 2022 |
| Identification of the form of self-excited aerodynamic force of bridge deck based on machine learning S Laima, Z Zhang, X Jin, W Li, H Li Physics of Fluids 36 (1), 2024 | 6 | 2024 |
| Suppression of flow separation around a finite wall-mounted square cylinder by suction at the side leading edge X Jin, M Dai, X Zou, S Laima Physics of Fluids 36 (1), 2024 | 4 | 2024 |
| Large-scale flow field super-resolution via local-global fusion convolutional neural networks X Zhou, X Jin, S Laima, H Li Physics of Fluids 36 (5), 2024 | 3 | 2024 |
| An invariance constrained deep learning network for partial differential equation discovery C Chen, H Li, X Jin Physics of Fluids 36 (4), 2024 | 3 | 2024 |
| Efficient data-driven nonlinear system identification for structural health monitoring: A proof-of-principle study S Li, X Jin, S Laima, H Li Advances in Structural Engineering 27 (16), 2950-2961, 2024 | | 2024 |
| Spatiotemporal coupling deep neural network for time-resolved flow field reconstruction around a circular cylinder X Jin, M Xu, Y Yang, W Chen Physics of Fluids 36 (10), 2024 | | 2024 |