| Physics-guided deep markov models for learning nonlinear dynamical systems with uncertainty W Liu, Z Lai, K Bacsa, E Chatzi Mechanical Systems and Signal Processing 178, 109276, 2022 | 27 | 2022 |
| Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures Z Lai, W Liu, X Jian, K Bacsa, L Sun, E Chatzi Data-Centric Engineering 3, e34, 2022 | 7* | 2022 |
| Neural extended Kalman filters for learning and predicting dynamics of structural systems W Liu, Z Lai, K Bacsa, E Chatzi Structural Health Monitoring 23 (2), 1037-1052, 2024 | 5 | 2024 |
| Symplectic encoders for physics-constrained variational dynamics inference K Bacsa, Z Lai, W Liu, M Todd, E Chatzi Scientific Reports 13 (1), 2643, 2023 | 5 | 2023 |
| A Physics-Guided Deep Learning Approach to Modeling Nonlinear Dynamics: A Case Study of a Bouc-Wen System W Liu, Z Lai, E Chatzi STRUCTURAL HEALTH MONITORING 2021, 2021 | 1 | 2021 |
| Discussing the Spectra of Physics-Enhanced Machine Learning via a Survey on Structural Mechanics Applications M Haywood-Alexander, W Liu, K Bacsa, Z Lai, E Chatzi arXiv preprint arXiv:2310.20425, 2023 | | 2023 |
| Symplectic encoders for variational inference in nonlinear dynamics systems K Bacsa, Z Lai, W Liu, E Chatzi Proceedings of ISMA2022 including USD2022, 2536-2549, 2023 | | 2023 |
| Physics Enhanced Machine Learning for Monitoring and Twinning M HAYWOOD-ALEXANDER, K BACSA, WEI LIU, Z LAI, E CHATZI STRUCTURAL HEALTH MONITORING 2023, 2023 | | 2023 |
| Model-based Unknown Input Estimation via Partially Observable Markov Decision Processes W Liu, Z Lai, CD Stoura, K Bacsa, E Chatzi ICLR 2023 Workshop on Physics for Machine Learning, 2022 | | 2022 |
| Symplectic encoders for variational inference in nonlinear systems K Bacsa, Z Lai, W Liu, E Chatzi 30th International Conference on Noise and Vibration Engineering (ISMA 2022 …, 2022 | | 2022 |
Zhilu LaiAssistant Professor, HKUST(GZ), HKUSTVerified email at ust.hk
