Zhang, Michael Minyi

11 publications

TMLR 2026 A Bayesian Bootstrap Framework for Mutual Information Neural Estimation: Bridging Classical Mutual Information Learning and Bayesian Nonparametric Learning Forough Fazeli-Asl, Michael Minyi Zhang, Linglong Kong, Bei Jiang

ICLR 2026 A Bayesian Nonparametric Framework for Private, Fair, and Balanced Tabular Data Synthesis Forough Fazeli-Asl, Michael Minyi Zhang, Linglong Kong, Bei Jiang

ICLR 2026 Revisiting Nonstationary Kernel Design for Multi-Output Gaussian Processes Qiaochu Xu, Zi Yang, Ying Li, Michael Minyi Zhang, Pablo M. Olmos

MLJ 2025 Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson

NeurIPS 2025 Multi-View Oriented GPLVM: Expressiveness and Efficiency Zi Yang, Ying Li, Zhidi Lin, Michael Minyi Zhang, Pablo M. Olmos

AISTATS 2025 Online Student-$t$ Processes with an Overall-Local Scale Structure for Modelling Non-Stationary Data Taole Sha, Michael Minyi Zhang

TMLR 2024 A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin

NeurIPSW 2024 Bayesian Nonparametric Learning Using the Maximum Mean Discrepancy Measure for Synthetic Data Generation Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin

ICML 2024 Preventing Model Collapse in Gaussian Process Latent Variable Models Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang

JMLR 2020 A New Class of Time Dependent Latent Factor Models with Applications Sinead A. Williamson, Michael Minyi Zhang, Paul Damien

JMLR 2019 Embarrassingly Parallel Inference for Gaussian Processes Michael Minyi Zhang, Sinead A. Williamson