Michael Minyi Zhang

Orcid: 0000-0002-5994-6496

According to our database1, Michael Minyi Zhang authored at least 22 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Accelerated algorithms for convex and non-convex optimization on manifolds.
Mach. Learn., March, 2025

A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation.
CoRR, March, 2025

Multi-View Oriented GPLVM: Expressiveness and Efficiency.
CoRR, February, 2025

Online Student-t Processes with an Overall-local Scale Structure for Modelling Non-stationary Data.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks.
Trans. Mach. Learn. Res., 2024

Scalable Random Feature Latent Variable Models.
CoRR, 2024

Preventing Model Collapse in Gaussian Process Latent Variable Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Sequential Gaussian Processes for Online Learning of Nonstationary Functions.
IEEE Trans. Signal Process., 2023

A Bayesian Non-parametric Approach to Generative Models: Integrating Variational Autoencoder and Generative Adversarial Networks using Wasserstein and Maximum Mean Discrepancy.
CoRR, 2023

Bayesian Non-linear Latent Variable Modeling via Random Fourier Features.
CoRR, 2023

A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks.
CoRR, 2023

Overcoming Posterior Collapse in Variational Autoencoders Via EM-Type Training.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Accelerated parallel non-conjugate sampling for Bayesian non-parametric models.
Stat. Comput., 2022

Sparse Infinite Random Feature Latent Variable Modeling.
CoRR, 2022

2021
Latent variable modeling with random features.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
A New Class of Time Dependent Latent Factor Models with Applications.
J. Mach. Learn. Res., 2020

Distributed, partially collapsed MCMC for Bayesian Nonparametrics.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Probabilistic Time of Arrival Localization.
IEEE Signal Process. Lett., 2019

Embarrassingly Parallel Inference for Gaussian Processes.
J. Mach. Learn. Res., 2019

2018
Robust and parallel Bayesian model selection.
Comput. Stat. Data Anal., 2018

Communication Efficient Parallel Algorithms for Optimization on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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