Michael Minyi Zhang | DeepAI

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Featured Co-authors

Eric P Xing
147 publications
David B. Dunson
94 publications
Henry Lam
49 publications
Lizhen Lin
38 publications
Fernando Perez-Cruz
35 publications
Barbara E. Engelhardt
28 publications
Avinava Dubey
21 publications
Pablo M. Olmos
20 publications
Sinead A. Williamson
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Bianca Dumitrascu
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Howard Huang
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∙ 08/27/2023

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

Generative models have emerged as a promising technique for producing hi...

0 Forough Fazeli Asl, et al. ∙

∙ 06/14/2023

Bayesian Non-linear Latent Variable Modeling via Random Fourier Features

The Gaussian process latent variable model (GPLVM) is a popular probabil...

0 Michael Minyi Zhang, et al. ∙

∙ 03/05/2023

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

A classic inferential problem in statistics is the two-sample hypothesis...

0 Forough Fazeli Asl, et al. ∙

∙ 05/20/2022

Sparse Infinite Random Feature Latent Variable Modeling

We propose a non-linear, Bayesian non-parametric latent variable model w...

0 Michael Minyi Zhang, et al. ∙

∙ 10/18/2020

Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds

We propose a general scheme for solving convex and non-convex optimizati...

22 Lizhen Lin, et al. ∙

∙ 06/19/2020

Latent variable modeling with random features

Gaussian process-based latent variable models are flexible and theoretic...

18 Gregory W. Gundersen, et al. ∙

∙ 01/15/2020

Distributed, partially collapsed MCMC for Bayesian Nonparametrics

Bayesian nonparametric (BNP) models provide elegant methods for discover...

33 Avinava Dubey, et al. ∙

∙ 10/15/2019

Probabilistic Time of Arrival Localization

In this paper, we take a new approach for time of arrival geo-localizati...

0 Fernando Perez-Cruz, et al. ∙

∙ 05/24/2019

Sequential Gaussian Processes for Online Learning of Nonstationary Functions

Many machine learning problems can be framed in the context of estimatin...

16 Michael Minyi Zhang, et al. ∙

∙ 04/18/2019

A New Class of Time Dependent Latent Factor Models with Applications

In many applications, observed data are influenced by some combination o...

0 Sinead A. Williamson, et al. ∙

∙ 10/26/2018

Communication Efficient Parallel Algorithms for Optimization on Manifolds

The last decade has witnessed an explosion in the development of models,...

0 Bayan Saparbayeva, et al. ∙

∙ 05/19/2017

Accelerated Inference for Latent Variable Models

Inference of latent feature models in the Bayesian nonparametric setting...

0 Michael Minyi Zhang, et al. ∙

∙ 10/19/2016

Robust and Parallel Bayesian Model Selection

Effective and accurate model selection is an important problem in modern...

0 Michael Minyi Zhang, et al. ∙

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