| Convergence analysis of distributed stochastic gradient descent with shuffling Q Meng, W Chen, Y Wang, ZM Ma, TY Liu Neurocomputing 337, 46-57, 2019 | 151 | 2019 |
| Finite sample analysis of the GTD policy evaluation algorithms in Markov setting Y Wang, W Chen, Y Liu, ZM Ma, TY Liu Advances in Neural Information Processing Systems 30, 2017 | 47 | 2017 |
| Target transfer Q-learning and its convergence analysis Y Wang, Y Liu, W Chen, ZM Ma, TY Liu Neurocomputing 392, 11-22, 2020 | 44 | 2020 |
| The impact of large language models on scientific discovery: a preliminary study using gpt-4 MR AI4Science, MA Quantum arXiv preprint arXiv:2311.07361, 2023 | 40 | 2023 |
| Recent advances on machine learning for computational fluid dynamics: A survey H Wang, Y Cao, Z Huang, Y Liu, P Hu, X Luo, Z Song, W Zhao, J Liu, ... arXiv preprint arXiv:2408.12171, 2024 | 16 | 2024 |
| Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients L Ma, ET Rolls, X Liu, Y Liu, Z Jiao, Y Wang, W Gong, Z Ma, F Gong, ... Journal of molecular cell biology 11 (8), 678-687, 2019 | 15 | 2019 |
| Gradient information matters in policy optimization by back-propagating through model C Li, Y Wang, W Chen, Y Liu, ZM Ma, TY Liu International Conference on Learning Representations, 2021 | 12 | 2021 |
| DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows R Zhang, P Hu, Q Meng, Y Wang, R Zhu, B Chen, ZM Ma, TY Liu Physics of Fluids 34 (10), 2022 | 11 | 2022 |
| Neuralstagger: accelerating physics-constrained neural pde solver with spatial-temporal decomposition X Huang, W Shi, Q Meng, Y Wang, X Gao, J Zhang, TY Liu International Conference on Machine Learning, 13993-14006, 2023 | 10 | 2023 |
| Generalization error bounds for optimization algorithms via stability Q Meng, Y Wang, W Chen, T Wang, ZM Ma, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 10 | 2017 |
| How to control hydrodynamic force on fluidic pinball via deep reinforcement learning H Feng, Y Wang, H Xiang, Z Jin, D Fan Physics of Fluids 35 (4), 2023 | 9 | 2023 |
| Neural operator with regularity structure for modeling dynamics driven by SPDEs P Hu, Q Meng, B Chen, S Gong, Y Wang, W Chen, R Zhu, ZM Ma, TY Liu arXiv preprint arXiv:2204.06255, 2022 | 7 | 2022 |
| The scale-invariant space for attention layer in neural network Y Wang, Y Liu, ZM Ma Neurocomputing 392, 1-10, 2020 | 6 | 2020 |
| Making Better Decision by Directly Planning in Continuous Control J Zhu, Y Wang, L Wu, T Qin, W Zhou, TY Liu, H Li International Conference on Learning Representations, 2023 | 5 | 2023 |
| Better neural PDE solvers through data-free mesh movers P Hu, Y Wang, ZM Ma arXiv preprint arXiv:2312.05583, 2023 | 3 | 2023 |
| Deep latent regularity network for modeling stochastic partial differential equations S Gong, P Hu, Q Meng, Y Wang, R Zhu, B Chen, Z Ma, H Ni, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7740-7747, 2023 | 2 | 2023 |
| Incorporating NODE with pre-trained neural differential operator for learning dynamics S Gong, Q Meng, Y Wang, L Wu, W Chen, Z Ma, TY Liu Neurocomputing 528, 48-58, 2023 | 2 | 2023 |
| Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms X Su, Y Wang, J Zhu, M Yi, F Xu, Z Ma, Y Liu arXiv preprint arXiv:2502.03095, 2025 | 1 | 2025 |
| Wavelet Diffusion Neural Operator P Hu, R Wang, X Zheng, T Zhang, H Feng, R Feng, L Wei, Y Wang, ... arXiv preprint arXiv:2412.04833, 2024 | 1 | 2024 |
| Hr-extreme: A high-resolution dataset for extreme weather forecasting N Ran, P Xiao, Y Wang, W Shi, J Lin, Q Meng, R Allmendinger arXiv preprint arXiv:2409.18885, 2024 | 1 | 2024 |