Sparse-as-possible SVBRDF acquisition. - Zhiming Zhou 001; Guojun Chen; Yue Dong 001; David P. Wipf; Yong Yu 001; John M. Snyder; Xin Tong 001 (ACM Trans. Graph., 2016)

Unsupervised Diverse Colorization via Generative Adversarial Networks. - Yun Cao 002; Zhiming Zhou 001; Weinan Zhang 001; Yong Yu 001 (ECML/PKDD (1), 2017)

Learning to Design Games: Strategic Environments in Deep Reinforcement Learning. - Haifeng Zhang 002; Jun Wang 012; Zhiming Zhou 001; Weinan Zhang 001; Ying Wen 001; Yong Yu 001; Wenxin Li 005 (CoRR, 2017)

Generative Adversarial Nets with Labeled Data by Activation Maximization. - Zhiming Zhou 001; Shu Rong; Han Cai; Weinan Zhang 001; Yong Yu 001; Jun Wang 012 (CoRR, 2017)

Face Transfer with Generative Adversarial Network. - Runze Xu; Zhiming Zhou 001; Weinan Zhang 001; Yong Yu 001 (CoRR, 2017)

Activation Maximization Generative Adversarial Nets. - Zhiming Zhou 001; Han Cai; Shu Rong; Yuxuan Song; Kan Ren; Weinan Zhang 001; Jun Wang 012; Yong Yu 001 (ICLR (Poster), 2018)

Learning to Design Games: Strategic Environments in Reinforcement Learning. - Haifeng Zhang 002; Jun Wang 012; Zhiming Zhou 001; Weinan Zhang 001; Yin Wen; Yong Yu 001; Wenxin Li 005 (IJCAI, 2018)

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis. - Zhiming Zhou 001; Yuxuan Song; Lantao Yu; Yong Yu 001 (CoRR, 2018)

Guiding the One-to-One Mapping in CycleGAN via Optimal Transport. - Guansong Lu; Zhiming Zhou 001; Yuxuan Song; Kan Ren; Yong Yu 001 (AAAI, 2019)

AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods. - Zhiming Zhou 001; Qingru Zhang; Guansong Lu; Hongwei Wang 004; Weinan Zhang 001; Yong Yu 001 (ICLR (Poster), 2019)

Lipschitz Generative Adversarial Nets. - Zhiming Zhou 001; Jiadong Liang; Yuxuan Song; Lantao Yu; Hongwei Wang 004; Weinan Zhang 001; Yong Yu 001; Zhihua Zhang 004 (ICML, 2019)

Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence. - Yaoming Zhu; Juncheng Wan; Zhiming Zhou 001; Liheng Chen; Lin Qiu; Weinan Zhang 001; Xin Jiang 002; Yong Yu 001 (SIGIR, 2019)

Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs. - Zhiming Zhou 001; Jian Shen 003; Yuxuan Song; Weinan Zhang 001; Yong Yu 001 (CoRR, 2019)

Quantifying Exposure Bias for Neural Language Generation. - Tianxing He; Jingzhao Zhang; Zhiming Zhou 001; James R. Glass (CoRR, 2019)

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck. - Yuxuan Song; Lantao Yu; Zhangjie Cao; Zhiming Zhou 001; Jian Shen 003; Shuo Shao 001; Weinan Zhang 001; Yong Yu 001 (ECAI, 2020)

Quality of Experience Evaluation for Streaming Video Using CGNN. - Zhiming Zhou 001; Yu Dong; Li Song 001; Rong Xie; Lin Li 062; Bing Zhou (VCIP, 2020)

Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency. - Guansong Lu; Zhiming Zhou 001; Jian Shen 003; Cheng Chen 015; Weinan Zhang 001; Yong Yu 001 (CoRR, 2020)

Sobolev Wasserstein GAN. - Minkai Xu; Zhiming Zhou 001; Guansong Lu; Jian Tang 005; Weinan Zhang 001; Yong Yu 001 (CoRR, 2020)

Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? - Tianxing He; Jingzhao Zhang; Zhiming Zhou 001; James R. Glass (EMNLP (1), 2021)