| Epidemic analysis of COVID-19 in China by dynamical modeling L Peng, W Yang, D Zhang, C Zhuge, L Hong arXiv preprint arXiv:2002.06563, 2020 | 738 | 2020 |
| Rational evaluation of various epidemic models based on the COVID-19 data of China W Yang, D Zhang, L Peng, C Zhuge, L Hong Epidemics 37, 100501, 2021 | 111 | 2021 |
| Epidemic analysis of COVID-19 in China by dynamical modeling (2020) L Peng, W Yang, D Zhang, C Zhuge, L Hong arXiv preprint arXiv:2002.06563, 2002 | 72 | 2002 |
| Revealing hidden dynamics from time-series data by ODENet P Hu, W Yang, Y Zhu, L Hong Journal of Computational Physics 461, 111203, 2022 | 45 | 2022 |
| Epidemic analysis of COVID-19 in China by dynamical modeling. arXiv L Peng, W Yang, D Zhang, C Zhuge, L Hong arXiv preprint arXiv:2002.06563, 2020 | 33 | 2020 |
| Differential Modulation of the Aggregation of N‐Terminal Truncated Aβ using Cucurbiturils G Li, WY Yang, YF Zhao, YX Chen, L Hong, YM Li Chemistry–A European Journal 24 (51), 13647-13653, 2018 | 21 | 2018 |
| When machine learning meets multiscale modeling in chemical reactions W Yang, L Peng, Y Zhu, L Hong The Journal of Chemical Physics 153 (9), 2020 | 16 | 2020 |
| Prediction of amyloid aggregation rates by machine learning and feature selection W Yang, P Tan, X Fu, L Hong The Journal of Chemical Physics 151 (8), 2019 | 13 | 2019 |
| Inhibitory Effects of Sulfated Polysaccharides from the Sea Cucumber Cucumaria Frondosa against Aβ40 Aggregation and Cytotoxicity G Li, Y Zhou, WY Yang, C Zhang, L Hong, L Jia ACS Chemical Neuroscience 12 (11), 1854-1859, 2021 | 12 | 2021 |
| Rational design of a cocktail of inhibitors against Aβ aggregation G Li, WY Yang, WH Li, YY Luo, YJ Lim, Y Li, A Paul, D Segal, L Hong, ... Chemistry–A European Journal 26 (16), 3499-3503, 2020 | 11 | 2020 |
| Epidemic analysis of COVID-19 in China by dynamical modeling [Internet] L Peng, W Yang, D Zhang, C Zhuge, L Hong arXiv preprint arXiv:2002.06563, 2020 | 6 | 2020 |
| Entropy structure informed learning for solving inverse problems of differential equations Y Jiang, W Yang, Y Zhu, L Hong Chaos, Solitons & Fractals 175, 114057, 2023 | 2 | 2023 |
| Identification of hydrodynamic instability by convolutional neural networks W Yang, L Peng, Y Zhu, L Hong arXiv preprint arXiv:2006.01446, 2020 | 1 | 2020 |
| Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Y Shi, W Yang, L Hong arXiv preprint arXiv:2501.00714, 2025 | | 2025 |
| MEP-Net: Generating Solutions to Scientific Problems with Limited Knowledge by Maximum Entropy Principle W Yang, L Peng, G Li, L Hong arXiv preprint arXiv:2412.02090, 2024 | | 2024 |
| Thermodynamics for Reduced Models of Breakable Amyloid Filaments Based on Maximum Entropy Principle X Zhang, H Jia, W Yang, L Peng, L Hong arXiv preprint arXiv:2409.05881, 2024 | | 2024 |
| A data-driven analysis on the mediation effect of compartment models between control measures and COVID-19 epidemics D Zhang, W Yang, W Wen, L Peng, C Zhuge, L Hong Heliyon 10 (13), 2024 | | 2024 |
| Entropy Structure Informed Learning for Inverse XDE Problems Y Jiang, W Yang, Y Zhu, L Hong arXiv preprint arXiv:2306.08241, 2023 | | 2023 |
| Incorporating continuous dependence implies better generalization ability G Li, S Ran, W Yang, L HONG | | |
| Stwcr: Weak Collocation Regression for Revealing Hidden Stochastic Dynamics from Single Trajectory Data Y Jiang, Z Zeng, W Yang, L Hong, Y Zhu Available at SSRN 5080262, 0 | | |
