Unsupervised Domain Adaptation via Calibrating Uncertainties. - Ligong Han; Yang Zou; Ruijiang Gao; Lezi Wang; Dimitris N. Metaxas (CVPR Workshops, 2019)

Cost-Accuracy Aware Adaptive Labeling for Active Learning. - Ruijiang Gao; Maytal Saar-Tsechansky (AAAI, 2020)

Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons. - Ligong Han; Ruijiang Gao; Mun Kim; Xin Tao; Bo Liu 005; Dimitris N. Metaxas (AAAI, 2020)

Dual Projection Generative Adversarial Networks for Conditional Image Generation. - Ligong Han; Martin Renqiang Min; Anastasis Stathopoulos; Yu Tian 003; Ruijiang Gao; Asim Kadav; Dimitris N. Metaxas (ICCV, 2021)

Human-AI Collaboration with Bandit Feedback. - Ruijiang Gao; Maytal Saar-Tsechansky; Maria De-Arteaga; Ligong Han; Min Kyung Lee; Matthew Lease (IJCAI, 2021)

Identifying Best Fair Intervention. - Ruijiang Gao; Han Feng (CoRR, 2021)

Loss Functions for Discrete Contextual Pricing with Observational Data. - Max Biggs; Ruijiang Gao; Wei Sun 031 (CoRR, 2021)

Enhancing Counterfactual Classification via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (CoRR, 2021)

Enhancing Counterfactual Classification Performance via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (AAAI, 2022)

AE-StyleGAN: Improved Training of Style-Based Auto-Encoders. - Ligong Han; Sri Harsha Musunuri; Martin Renqiang Min; Ruijiang Gao; Yu Tian 003; Dimitris N. Metaxas (WACV, 2022)

Probabilistic Conformal Prediction Using Conditional Random Samples. - Zhendong Wang; Ruijiang Gao; Mingzhang Yin; Mingyuan Zhou; David M. Blei (AISTATS, 2023)

On the Impact of Algorithmic Recourse on Social Segregation. - Ruijiang Gao; Himabindu Lakkaraju (ICML, 2023)

Learning Complementary Policies for Human-AI Teams. - Ruijiang Gao; Maytal Saar-Tsechansky; Maria De-Arteaga; Ligong Han; Wei Sun 031; Min Kyung Lee; Matthew Lease (CoRR, 2023)

Improving Tuning-Free Real Image Editing with Proximal Guidance. - Ligong Han; Song Wen 001; Qi Chen; Zhixing Zhang; Kunpeng Song; Mengwei Ren; Ruijiang Gao; Yuxiao Chen 002; Di Liu 003; Qilong Zhangli; Anastasis Stathopoulos; Jindong Jiang; et al. (CoRR, 2023)

Confounding-Robust Policy Improvement with Human-AI Teams. - Ruijiang Gao; Mingzhang Yin (CoRR, 2023)

Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design. - Mingzhang Yin; Ruijiang Gao; Weiran Lin; Steven M. Shugan (CoRR, 2023)

SEL-BALD: Deep Bayesian Active Learning with Selective Labels. - Ruijiang Gao; Mingzhang Yin; Maytal Saar-Tsechansky (NeurIPS, 2024)

ProxEdit: Improving Tuning-Free Real Image Editing with Proximal Guidance. - Ligong Han; Song Wen 001; Qi Chen; Zhixing Zhang; Kunpeng Song; Mengwei Ren; Ruijiang Gao; Anastasis Stathopoulos; Xiaoxiao He; Yuxiao Chen 002; Di Liu 003; Qilong Zhangli; et al. (WACV, 2024)

Adjusting regression models for conditional uncertainty calibration. - Ruijiang Gao; Mingzhang Yin; James McInerney; Nathan Kallus (Mach. Learn., 2024)

Confounding-Robust Deferral Policy Learning. - Ruijiang Gao; Mingzhang Yin (AAAI, 2025)

HR-Bandit: Human-AI Collaborated Linear Recourse Bandit. - Junyu Cao; Ruijiang Gao; Esmaeil Keyvanshokooh (AISTATS, 2025)