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Zhiming Zhou
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Cited by
Year
Unsupervised Diverse Colorization via Generative Adversarial Networks
Y Cao, Z Zhou, W Zhang, Y Yu
ECML, 2017, 2017
1392017
Activation Maximization Generative Adversarial Nets
Z Zhou, H Cai, S Rong, Y Song, K Ren, W Zhang, Y Yu, J Wang
ICLR, 2018, 2017
76*2017
Lipschitz Generative Adversarial Nets
Z Zhou, J Liang, Y Song, L Yu, H Wang, W Zhang, Y Yu, Z Zhang
ICML, 2019, 2019
69*2019
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Z Zhou, Q Zhang, G Lu, H Wang, W Zhang, Y Yu
ICLR, 2019, 2018
432018
Sparse-as-Possible SVBRDF acquisition
Z Zhou, G Chen, Y Dong, D Wipf, Y Yu, J Snyder, X Tong
SIGGRAPH Asia, 2016, ACM Transactions on Graphics (TOG), 2016, 2016
362016
Quantifying exposure bias for neural language generation
T He, J Zhang, Z Zhou, J Glass
30*2019
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Z Yaoming, W Juncheng, Z Zhiming, C Liheng, Q Lin, Z Weinan, J Xin, ...
SIGIR, 2019, 2019
21*2019
Guiding the One-to-one Mapping in CycleGAN via Optimal Transport
G Lu, Z Zhou, Y Song, K Ren, Y Yu
AAAI, 2019, 2018
152018
Learning to Design Games: Strategic Environments in Deep Reinforcement Learning
H Zhang, J Wang, Z Zhou, W Zhang, Y Wen, Y Yu, W Li
IJCAI, 2018, 2017
12*2017
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Y Song, L Yu, Z Cao, Z Zhou, J Shen, S Shao, W Zhang, Y Yu
ECAI, 2019, 2019
62019
Towards Generalized Implementation of Wasserstein Distance in GANs
M Xu, Z Zhou, G Lu, J Tang, W Zhang, Y Yu
AAAI, 2021, 2021
42021
Large-Scale Optimal Transport with Cycle-Consistency
G Lu, Z Zhou, J Shen, C Chen, W Zhang, Y Yu
arXiv preprint arXiv:2003.06635, 2020
22020
Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs
Z Zhou, J Shen, Y Song, W Zhang, Y Yu
arXiv preprint arXiv:1904.01184, 2019
22019
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Articles 1–13