Adversarial Learning of a Sampler Based on an Unnormalized Distribution. - Chunyuan Li; Ke Bai 001; Jianqiao Li; Guoyin Wang 002; Changyou Chen; Lawrence Carin (AISTATS, 2019)

GO Gradient for Expectation-Based Objectives. - Yulai Cong; Miaoyun Zhao; Ke Bai 001; Lawrence Carin (ICLR (Poster), 2019)

Variational Annealing of GANs: A Langevin Perspective. - Chenyang Tao; Shuyang Dai; Liqun Chen 001; Ke Bai 001; Junya Chen; Chang Liu 030; Ruiyi Zhang 002; Georgiy V. Bobashev; Lawrence Carin (ICML, 2019)

On Fenchel Mini-Max Learning. - Chenyang Tao; Liqun Chen 001; Shuyang Dai; Junya Chen; Ke Bai 001; Dong Wang 037; Jianfeng Feng; Wenlian Lu; Georgiy V. Bobashev; Lawrence Carin (NeurIPS, 2019)

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. - Liqun Chen 001; Ke Bai 001; Chenyang Tao; Yizhe Zhang 002; Guoyin Wang 002; Wenlin Wang; Ricardo Henao; Lawrence Carin (AAAI, 2020)

Advancing weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (BMVC, 2020)

Semantic Matching via Optimal Partial Transport. - Ruiyi Zhang 002; Changyou Chen; Xinyuan Zhang 001; Ke Bai 001; Lawrence Carin (EMNLP (Findings), 2020)

Regularizing Reasons for Outfit Evaluation with Gradient Penalty. - Xingxing Zou; Zhizhong Li 002; Ke Bai 001; Dahua Lin; Waikeung Wong (CoRR, 2020)

Weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (CoRR, 2020)

Variational Inference with Holder Bounds. - Junya Chen; Danni Lu; Zidi Xiu; Ke Bai 001; Lawrence Carin; Chenyang Tao (CoRR, 2021)

Open World Classification with Adaptive Negative Samples. - Ke Bai 001; Guoyin Wang 002; Jiwei Li 001; Sunghyun Park; Sungjin Lee; Puyang Xu; Ricardo Henao; Lawrence Carin (EMNLP, 2022)

Learning to Weight Filter Groups for Robust Classification. - Siyang Yuan; Yitong Li 001; Dong Wang 037; Ke Bai 001; Lawrence Carin; David E. Carlson (WACV, 2022)

Collaborative Anomaly Detection. - Ke Bai 001; Aonan Zhang; Zhizhong Li 002; Ricardo Henao; Chong Wang 002; Lawrence Carin (CoRR, 2022)

Estimating Total Correlation with Mutual Information Estimators. - Ke Bai 001; Pengyu Cheng; Weituo Hao; Ricardo Henao; Larry Carin (AISTATS, 2023)

OssCSE: Overcoming Surface Structure Bias in Contrastive Learning for Unsupervised Sentence Embedding. - Zhan Shi; Guoyin Wang 002; Ke Bai 001; Jiwei Li 001; Xiang Li; Qingjun Cui; Belinda Zeng; Trishul Chilimbi; Xiaodan Zhu 001 (EMNLP, 2023)

Everyone Deserves A Reward: Learning Customized Human Preferences. - Pengyu Cheng; Jiawen Xie; Ke Bai 001; Yong Dai 001; Nan Du (CoRR, 2023)

Learning in the Open World: Techniques for Identifying and Adapting to the Unknown. - Ke Bai 001 (2023)

Multiscale Visual-Attribute Co-Attention for Zero-Shot Image Recognition. - Hao Zhang 050; Long Tian; Zhengjue Wang; Yishi Xu; Pengyu Cheng; Ke Bai 001; Bo Chen 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)