| Convolutional neural networks with low-rank regularization C Tai, T Xiao, Y Zhang, X Wang arXiv preprint arXiv:1511.06067, 2015 | 493 | 2015 |
| Stochastic modified equations and adaptive stochastic gradient algorithms Q Li, C Tai, E Weinan International Conference on Machine Learning, 2101-2110, 2017 | 263 | 2017 |
| Maximum principle based algorithms for deep learning Q Li, L Chen, C Tai, E Weinan Journal of Machine Learning Research 18 (165), 1-29, 2018 | 208 | 2018 |
| Stochastic modified equations and dynamics of stochastic gradient algorithms i: Mathematical foundations Q Li, C Tai, E Weinan The Journal of Machine Learning Research 20 (1), 1474-1520, 2019 | 123 | 2019 |
| Understanding and enhancing the transferability of adversarial examples L Wu, Z Zhu, C Tai arXiv preprint arXiv:1802.09707, 2018 | 100 | 2018 |
| DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants M Wang, C Tai, W E, L Wei Nucleic acids research 46 (11), e69-e69, 2018 | 94 | 2018 |
| Wavelet frame based multiphase image segmentation C Tai, X Zhang, Z Shen SIAM Journal on Imaging Sciences 6 (4), 2521-2546, 2013 | 37 | 2013 |
| Dynamics of stochastic gradient algorithms Q Li, C Tai, E Weinan arXiv preprint arXiv:1511.06251, 2015 | 27 | 2015 |
| Multiscale adaptive representation of signals: I. the basic framework C Tai, E Weinan The Journal of Machine Learning Research 17 (1), 4875-4912, 2016 | 19 | 2016 |
| Approximation analysis of convolutional neural networks C Bao, Q Li, Z Shen, C Tai, L Wu, X Xiang work 65, 2014 | 15 | 2014 |
Qianxiao LiAssistant Professor, Department of Mathematics and Institute for Functional Intelligent MaterialsVerified email at nus.edu.sg
