Communication Efficient Parallel Algorithms for Optimization on Manifolds. - Bayan Saparbayeva; Michael Minyi Zhang; Lizhen Lin (NeurIPS, 2018)

Robust and parallel Bayesian model selection. - Michael Minyi Zhang; Henry Lam; Lizhen Lin (Comput. Stat. Data Anal., 2018)

Embarrassingly Parallel Inference for Gaussian Processes. - Michael Minyi Zhang; Sinead A. Williamson (J. Mach. Learn. Res., 2019)

Probabilistic Time of Arrival Localization. - Fernando Pérez-Cruz; Pablo M. Olmos; Michael Minyi Zhang; Howard Huang (IEEE Signal Process. Lett., 2019)

Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes. - Li-Fang Cheng; Bianca Dumitrascu; Michael Minyi Zhang; Corey Chivers; Michael Draugelis; Kai Li 001; Barbara E. Engelhardt (AISTATS, 2020)

Distributed, partially collapsed MCMC for Bayesian Nonparametrics. - Kumar Avinava Dubey; Michael Minyi Zhang; Eric P. Xing; Sinead Williamson (AISTATS, 2020)

A New Class of Time Dependent Latent Factor Models with Applications. - Sinead A. Williamson; Michael Minyi Zhang; Paul Damien (J. Mach. Learn. Res., 2020)

Latent variable modeling with random features. - Gregory W. Gundersen; Michael Minyi Zhang; Barbara E. Engelhardt (AISTATS, 2021)

Sparse Infinite Random Feature Latent Variable Modeling. - Michael Minyi Zhang (CoRR, 2022)

Accelerated parallel non-conjugate sampling for Bayesian non-parametric models. - Michael Minyi Zhang; Sinead A. Williamson; Fernando Pérez-Cruz (Stat. Comput., 2022)

Overcoming Posterior Collapse in Variational Autoencoders Via EM-Type Training. - Ying Li; Lei Cheng 003; Feng Yin; Michael Minyi Zhang; Sergios Theodoridis (ICASSP, 2023)

A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks. - Forough Fazeli-Asl; Michael Minyi Zhang; Lizhen Lin (CoRR, 2023)

Bayesian Non-linear Latent Variable Modeling via Random Fourier Features. - Michael Minyi Zhang; Gregory W. Gundersen; Barbara E. Engelhardt (CoRR, 2023)

A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy. - Forough Fazeli-Asl; Michael Minyi Zhang (CoRR, 2023)

Sequential Gaussian Processes for Online Learning of Nonstationary Functions. - Michael Minyi Zhang; Bianca Dumitrascu; Sinead A. Williamson; Barbara E. Engelhardt (IEEE Trans. Signal Process., 2023)

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

Scalable Random Feature Latent Variable Models. - Ying Li; Zhidi Lin; Yuhao Liu 002; Michael Minyi Zhang; Pablo M. Olmos; Petar M. Djuric (CoRR, 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 (Trans. Mach. Learn. Res., 2024)

Online Student-t Processes with an Overall-local Scale Structure for Modelling Non-stationary Data. - Taole Sha; Michael Minyi Zhang (AISTATS, 2025)

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

A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation. - Forough Fazeli-Asl; Michael Minyi Zhang; Bei Jiang; Linglong Kong (CoRR, 2025)

Accelerated algorithms for convex and non-convex optimization on manifolds. - Lizhen Lin; Bayan Saparbayeva; Michael Minyi Zhang; David B. Dunson (Mach. Learn., 2025)