| Multisource selective transfer framework in multiobjective optimization problems J Zhang, W Zhou, X Chen, W Yao, L Cao IEEE Transactions on Evolutionary Computation 24 (3), 424-438, 2019 | 71 | 2019 |
| Fca: Learning a 3d full-coverage vehicle camouflage for multi-view physical adversarial attack D Wang, T Jiang, J Sun, W Zhou, Z Gong, X Zhang, W Yao, X Chen Proceedings of the AAAI Conference on Artificial Intelligence 36 (2), 2414-2422, 2022 | 62 | 2022 |
| Strong convergence rate of splitting schemes for stochastic nonlinear Schrödinger equations J Cui, J Hong, Z Liu, W Zhou Journal of Differential Equations 266 (9), 5625-5663, 2019 | 62 | 2019 |
| TONR: An exploration for a novel way combining neural network with topology optimization Z Zhang, Y Li, W Zhou, X Chen, W Yao, Y Zhao Computer Methods in Applied Mechanics and Engineering 386, 114083, 2021 | 53 | 2021 |
| The heat source layout optimization using deep learning surrogate modeling X Chen, X Chen, W Zhou, J Zhang, W Yao Structural and Multidisciplinary Optimization 62 (6), 3127-3148, 2020 | 52 | 2020 |
| A novel meta-learning initialization method for physics-informed neural networks X Liu, X Zhang, W Peng, W Zhou, W Yao arXiv preprint arXiv:2107.10991, 2021 | 38 | 2021 |
| A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout X Chen, X Zhao, Z Gong, J Zhang, W Zhou, X Chen, W Yao arXiv preprint arXiv:2103.11177, 2021 | 34 | 2021 |
| Accelerating physics-informed neural network training with prior dictionaries W Peng, W Zhou, J Zhang, W Yao arXiv preprint arXiv:2004.08151, 2020 | 33 | 2020 |
| Stochastic symplectic and multi-symplectic methods for nonlinear Schrödinger equation with white noise dispersion J Cui, J Hong, Z Liu, W Zhou Journal of Computational Physics 342, 267-285, 2017 | 33 | 2017 |
| Temperature field inversion of heat-source systems via physics-informed neural networks X Liu, W Peng, Z Gong, W Zhou, W Yao Engineering Applications of Artificial Intelligence 113, 104902, 2022 | 25 | 2022 |
| Projection methods for stochastic differential equations with conserved quantities W Zhou, L Zhang, J Hong, S Song arXiv preprint arXiv:1601.04157, 2016 | 25 | 2016 |
| Stochastic symplectic Runge-Kutta methods for the strong approximation of Hamiltonian systems with additive noise W Zhou, J Zhang, J Hong, S Song arXiv preprint arXiv:1601.04161, 2016 | 20 | 2016 |
| Average vector field methods for the coupled Schrödinger—KdV equations H Zhang, SH Song, XD Chen, WE Zhou Chinese Physics B 23 (7), 070208, 2014 | 20 | 2014 |
| Rang: A residual-based adaptive node generation method for physics-informed neural networks W Peng, W Zhou, X Zhang, W Yao, Z Liu arXiv preprint arXiv:2205.01051, 2022 | 18 | 2022 |
| IDRLnet: A Physics-Informed Neural Network Library W Peng, J Zhang, W Zhou, X Zhao, W Yao, X Chen arXiv preprint arXiv:2107.04320, 2021 | 18 | 2021 |
| Conformal structure-preserving method for damped nonlinear Schrödinger equation H Fu, WE Zhou, X Qian, SH Song, LY Zhang Chinese Physics B 25 (11), 110201, 2016 | 18 | 2016 |
| Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network Y Zhang, Z Gong, W Zhou, X Zhao, X Zheng, W Yao arXiv preprint arXiv:2301.06674, 2023 | 13 | 2023 |
| Hybrid finite difference with the physics-informed neural network for solving pde in complex geometries Z Xiang, W Peng, W Zhou, W Yao arXiv preprint arXiv:2202.07926, 2022 | 13 | 2022 |
| Multi-symplectic method for the coupled Schrödinger—KdV equations H Zhang, SH Song, WE Zhou, XD Chen Chinese Physics B 23 (8), 080204, 2014 | 12 | 2014 |
| An Improved Data-Driven Topology Optimization Method Using Feature Pyramid Networks with Physical Constraints J Luo, Y Li, W Zhou, Z Gong, Z Zhang, W Yao CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES 128 (3), 823-848, 2021 | 10 | 2021 |
Songhe SongDepartment of Mathematics, National University of Defense TechnologyVerified email at nudt.edu.cn
