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Cheng Tai
Cheng Tai
Moqi,Inc.
Verified email at moqi.ai
Title
Cited by
Cited by
Year
Convolutional neural networks with low-rank regularization
C Tai, T Xiao, Y Zhang, X Wang
arXiv preprint arXiv:1511.06067, 2015
4512015
Stochastic modified equations and adaptive stochastic gradient algorithms
Q Li, C Tai, E Weinan
International Conference on Machine Learning, 2101-2110, 2017
2502017
Maximum principle based algorithms for deep learning
Q Li, L Chen, C Tai
arXiv preprint arXiv:1710.09513, 2017
1872017
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
1022019
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
822018
Understanding and enhancing the transferability of adversarial examples
L Wu, Z Zhu, C Tai
arXiv preprint arXiv:1802.09707, 2018
802018
Wavelet frame based multiphase image segmentation
C Tai, X Zhang, Z Shen
SIAM Journal on Imaging Sciences 6 (4), 2521-2546, 2013
382013
Dynamics of stochastic gradient algorithms
Q Li, C Tai, E Weinan
arXiv preprint arXiv:1511.06251, 2015
212015
Multiscale adaptive representation of signals: I. the basic framework
C Tai, E Weinan
The Journal of Machine Learning Research 17 (1), 4875-4912, 2016
192016
Approximation analysis of convolutional neural networks
C Bao, Q Li, Z Shen, C Tai, L Wu, X Xiang
work 65, 2014
112014
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Articles 1–10