| Estimation of railway track longitudinal irregularity using vehicle response with information compression and Bayesian deep learning C Li, Q He, P Wang Computer‐Aided Civil and Infrastructure Engineering 37 (10), 1260-1276, 2022 | 39 | 2022 |
| Spatial–temporal model to identify the deformation of underlying high-speed railway infrastructure C Li, P Wang, T Gao, J Wang, C Yang, H Liu, Q He Journal of Transportation Engineering, Part A: Systems 146 (8), 04020084, 2020 | 21 | 2020 |
| Fault diagnosis for rolling bearings of a freight train under limited fault data: Few-shot learning method C Li, K Yang, H Tang, P Wang, J Li, Q He Journal of Transportation Engineering, Part A: Systems 147 (8), 04021041, 2021 | 16 | 2021 |
| High-speed railway track maintenance and irregularity rectification with coupling physical constraint of adjacent fasteners H Sun, C Li, L Zhao, F Yang, C Xu, P Wang, S Wan, Q He Construction and Building Materials 382, 131281, 2023 | 7 | 2023 |
| Railway tie deterioration interval estimation with Bayesian deep learning and data-driven maintenance strategy Q He, H Sun, M Dobhal, C Li, R Mohammadi Construction and Building Materials 342, 128040, 2022 | 7 | 2022 |
| A multitask learning method for rail corrugation detection using in-vehicle responses and noise data C Li, H Sun, W Li, Y Wang, Z Wan, W Wu, P Wang, Q He IEEE Transactions on Intelligent Transportation Systems 25 (6), 5045-5058, 2023 | 4 | 2023 |
