World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5248
World Ranking
10846
National Ranking
4514

Overview

Mingyuan Zhou is affiliated with The University of Texas at Austin in the United States. Their research primarily spans the field of Computer Science, with a particular focus on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Signal Processing, and Civil and Structural Engineering.

The scientist's work addresses multiple key topics within these disciplines. These include:

  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Generative Adversarial Networks and Image Synthesis
  • Multimodal Machine Learning Applications
  • Machine Learning and Data Classification
  • Gaussian Processes and Bayesian Inference
  • Advanced Graph Neural Networks

Mingyuan Zhou has contributed extensively to the academic literature with 200 publications in Computer Science. Their frequent publication venues include:

  • arXiv (Cornell University)
  • PubMed
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Biological Macromolecules

Selected recent papers demonstrate their involvement in diverse topics and methodologies, including generative models, signal processing, and biomedical research. Examples include:

  • "Diffusion-GAN: Training GANs with Diffusion," 2022, arXiv (Cornell University)
  • "Variational Temporal Deep Generative Model for Radar HRRP Target Recognition," 2020, IEEE Transactions on Signal Processing
  • "A mixture-density-based tandem optimization network for on-demand inverse design of thin-film high reflectors," 2021, Nanophotonics
  • "Disease Burden and Attributable Risk Factors of Alzheimer's Disease and Dementia in China from 1990 to 2019," 2022, The Journal of Prevention of Alzheimer's Disease
  • "Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning," 2022, arXiv (Cornell University)

Collaboration is also a notable aspect of Zhou's research profile. Frequent coauthors include Huangjie Zheng, Bo Chen, Shujian Zhang, Weizhu Chen, and Zhendong Wang. The collaboration counts with these researchers range from 10 to 23 joint works, indicating sustained partnerships.

Best Publications

  • Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

    Mingyuan Zhou;Haojun Chen;John Paisley;Lu Ren

  • Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations

    Mingyuan Zhou;Haojun Chen;Lu Ren;Guillermo Sapiro

  • Beta-Negative Binomial Process and Poisson Factor Analysis

    Mingyuan Zhou;Lauren A. Hannah;David B. Dunson;Lawrence Carin

  • Negative Binomial Process Count and Mixture Modeling

    Mingyuan Zhou;Lawrence Carin

  • Masking: A New Perspective of Noisy Supervision

    Bo Han;Jiangchao Yao;Gang Niu;Mingyuan Zhou

  • Infinite edge partition models for overlapping community detection and link prediction

    Mingyuan Zhou

  • Dictionary Learning for Noisy and Incomplete Hyperspectral Images

    Zhengming Xing;Mingyuan Zhou;Alexey Castrodad;Guillermo Sapiro

  • Lognormal and Gamma Mixed Negative Binomial Regression

    Mingyuan Zhou;Lingbo Li;Lawrence Carin;David B. Dunson

  • Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

    Unknown

  • Adversarially Adaptive Normalization for Single Domain Generalization

    Xinjie Fan;Qifei Wang;Junjie Ke;Feng Yang

  • Meta-Learning without Memorization

    Mingzhang Yin;George Tucker;Mingyuan Zhou;Sergey Levine

  • Lognormal and Gamma Mixed Negative Binomial Regression

    Mingyuan Zhou;Lingbo Li;David Dunson;Lawrence Carin

  • A Bayesian Nonparametric Approach to Image Super-Resolution

    Gungor Polatkan;Mingyuan Zhou;Lawrence Carin;David Blei

  • Dependent Hierarchical Beta Process for Image Interpolation and Denoising

    Mingyuan Zhou;Hongxia Yang;Guillermo Sapiro;David B. Dunson

  • Semi-Implicit Variational Inference

    Mingzhang Yin;Mingyuan Zhou

  • Augmentable gamma belief networks

    Mingyuan Zhou;Yulai Cong;Bo Chen

  • Variational Graph Recurrent Neural Networks

    Ehsan Hajiramezanali;Arman Hasanzadeh;Nick Duffield;Krishna R Narayanan

  • Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

    Ayan Acharya;Joydeep Ghosh;Mingyuan Zhou

  • WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

    Hao Zhang;Bo Chen;Dandan Guo;Mingyuan Zhou

  • Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

    Estee Y Cramer;Evan L Ray;Velma K Lopez;Johannes Bracher

  • Semi-Implicit Graph Variational Auto-Encoders

    Arman Hasanzadeh;Ehsan Hajiramezanali;Krishna R. Narayanan;Nick Duffield

  • Bayesian Graph Neural Networks with Adaptive Connection Sampling

    Arman Hasanzadeh;Ehsan Hajiramezanali;Shahin Boluki;Nick Duffield

Frequent Co-Authors

Bo Chen
Bo Chen Xidian University
Lawrence Carin
Lawrence Carin Duke University
David B. Dunson
David B. Dunson Duke University
Hanna Wallach
Hanna Wallach Microsoft (United States)
Krishna R. Narayanan
Krishna R. Narayanan Texas A&M University
Guillermo Sapiro
Guillermo Sapiro Princeton University
Nick Duffield
Nick Duffield Texas A&M University
Wray Buntine
Wray Buntine VinUniversity
David M. Blei
David M. Blei Columbia University
Joydeep Ghosh
Joydeep Ghosh The University of Texas at Austin

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