Unsupervised Diverse Colorization via Generative Adversarial Networks Y Cao, Z Zhou, W Zhang, Y Yu ECML, 2017, 2017 | 176 | 2017 |
Activation Maximization Generative Adversarial Nets Z Zhou, H Cai, S Rong, Y Song, K Ren, W Zhang, Y Yu, J Wang ICLR, 2018, 2017 | 99 | 2017 |
Lipschitz Generative Adversarial Nets Z Zhou, J Liang, Y Song, L Yu, H Wang, W Zhang, Y Yu, Z Zhang ICML, 2019, 2019 | 80* | 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 | 50 | 2018 |
Quantifying exposure bias for neural language generation T He, J Zhang, Z Zhou, J Glass | 44* | 2019 |
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 | 43 | 2016 |
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 | 27* | 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 | 19 | 2018 |
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 | 15* | 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 | 11 | 2019 |
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 | 8 | 2020 |
Towards Generalized Implementation of Wasserstein Distance in GANs M Xu, Z Zhou, G Lu, J Tang, W Zhang, Y Yu AAAI, 2021, 2021 | 4 | 2021 |
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 | 4 | 2019 |