Probabilistic machine learning

Probabilistic Conformal Prediction Using Conditional Random Samples
Zhendong Wang*, Ruijiang Gao*, Mingzhang Yin* , Mingyuan Zhou, David M. Blei
Under review. Short version accepted by ICML 2022 Workshop DFUQ, Spotlight. pdf, code

Meta-Learning without Memorization
Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
International Conference on Learning Representations (ICLR), Spotlight, Top 5%. Short version in Meta-Learning Workshop, (NeurIPS MetaLearn). pdf, blog, code, poster, slides1, talk1, slides2, talk2

Probabilistic Best Subset Selection via Gradient-Based Optimization
Mingzhang Yin, Nhat Ho, Bowei Yan, Xiaoning Qian, Mingyuan Zhou
Under review. pdf, code

Semi-Implicit Variational Inference
Mingzhang Yin, Mingyuan Zhou
International Conference on Machine Learning (ICML), Long talk. pdf, slides, poster, code and talk

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

Semi-Implicit Generative Model
Mingzhang Yin, Mingyuan Zhou
Workshop on Bayesian Deep Learning, (NeurIPS BDL). pdf and poster

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

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 and poster