Selected Works
Conformal Sensitivity Analysis for Individual Treatment Effects
Mingzhang Yin, Claudia Shi, Yixin Wang, David M. Blei
Journal of the American Statistical Association (JASA). pdf, code, slides
Unraveling Multifaceted User Preferences on Content Platforms: A Bayesian Deep Learning Approach
Mingzhang Yin, Ziwei Cong, Jia Liu
Marketing Science, 2025.
Modeling Dynamic Consumer Preferences from Few-shot Data: A Meta-Learning Approach
Mingzhang Yin, Khaled Boughanmi, Anirban Mukherjee
Journal of Marketing Research (JMR), 2026.
Optimization-Based Causal Estimation from Heterogeneous Environments
Mingzhang Yin, Yixin Wang, David M. Blei
Journal of Machine Learning Research (JMLR). pdf, code, slides, SlidesLive
Meta-Learning without Memorization
Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
International Conference on Learning Representations (ICLR), Spotlight, Top 5%. pdf, blog, code, poster, slides1, talk1, slides2, talk2
Semi-Implicit Variational Inference
Mingzhang Yin, Mingyuan Zhou
International Conference on Machine Learning (ICML), Long talk, Top 2.8%. pdf, slides, poster, code and talk
Other Publications
Permutative Preference Alignment from Listwise Ranking of Human Judgments
Yang Zhao, Yixin Wang, Mingzhang Yin
Empirical Methods in Natural Language Processing (EMNLP), 2025.
SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection
Ruijiang Gao, Mingzhang Yin, Maytal Saar-Tsechansky
Advances in Neural Information Processing Systems
(NeurIPS). pdf, code
Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices
Ryan Dew, Nicolas Padilla, et al., and Mingzhang Yin.
International Journal of Research in Marketing (IJRM)
pdf, code
Confounding-Robust Deferral Policy Learning
Ruijiang Gao, Mingzhang Yin
AAAI Conference on Artificial Intelligence (AAAI), 2024.
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang
International Conference on Machine Learning (ICML). pdf, code
Adjusting Regression Models for Conditional Uncertainty Calibration
Ruijiang Gao, Mingzhang Yin, James Mcinerney, Nathan Kallus
Machine Learning Journal (MLJ). pdf, code
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping
Russell Z Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe’er, Simon Tavaré
AAAI Conference on Artificial Intelligence (AAAI). pdf, code
Probabilistic Conformal Prediction Using Conditional Random Samples
Zhendong Wang*, Ruijiang Gao*, Mingzhang Yin* , Mingyuan Zhou, David M. Blei
International Conference on Artificial Intelligence and Statistics (AISTATS). Short version accepted by ICML 2022 Workshop DFUQ, Spotlight. pdf, code
Partial Identification with Noisy Covariates: A Robust Optimization Approach
Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan
Causal Learning and Reasoning (CLeaR). pdf, code
A Theoretical Case Study of Structured Variational Inference for Community Detection
Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
International Conference on Artificial Intelligence and Statistics (AISTATS). pdf, slides, code
Topological Data Analysis in Digital Marketing
Choudur Lakshminarayan, Mingzhang Yin
Applied Stochastic Models in Business and Industry, 2020.
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
Mingzhang Yin* , Yuguang Yue*, Mingyuan Zhou
International Conference on Machine Learning (ICML). pdf, errata, code
Discrete Action On-Policy Learning with Action-Value Critic
Yuguang Yue, Yunhao Tang, Mingzhang Yin and Mingyuan Zhou
International Conference on Artificial Intelligence and Statistics (AISTATS). pdf, code
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks
Mingzhang Yin, Mingyuan Zhou
International Conference on Learning Representations (ICLR), Top 10%. pdf, code and slides
Convergence of Gradient EM on Multi-component Mixture of Gaussians
Bowei Yan, Mingzhang Yin, and Purnamrita Sarkar
Advances in Neural Information Processing Systems (NeurIPS). pdf, code and poster
Semi-Implicit Generative Model
Mingzhang Yin, Mingyuan Zhou
Workshop on Bayesian Deep Learning, (NeurIPS BDL). pdf and poster
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator
Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
The Conference on Uncertainty in Artificial Intelligence (UAI). pdf, code
Words That Matter: Analyzing the Causal Effect of Words
Alain Lemaire*, Mingzhang Yin*, Oded Netzer
SSRN. pdf
Probabilistic Best Subset Selection via Gradient-Based Optimization
Mingzhang Yin, Nhat Ho, Bowei Yan, Xiaoning Qian, Mingyuan Zhou
arXiv 2006.06448. pdf, code
Bayesian Invariance Modeling of Multi-Environment Data
Luhuan Wu, Mingzhang Yin, Yixin Wang, John Patrick Cunningham, David Blei
arXiv 2506.22675. pdf
Relaxation of Projected Prior with Continuous Gap Shrinkage
Leo L Duan, Sunghyun Cho, Mingzhang Yin
arXiv 2605.14936. pdf
*=equal contribution
