Mingyuan Zhou

Mingyuan Zhou, John Paisley, Lawrence Carin, 2009, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference pdf

Sriram Vishwanath, Mingyuan Zhou, Jonathan I. Tamir, 2020, AISTATS.

Probabilistic Margins for Instance Reweighting in Adversarial Training

Masashi Sugiyama, Mingyuan Zhou, M. Sugiyama, 2021, NeurIPS.

Contextual Dropout: An Efficient Sample-Dependent Dropout Module pdf

Xiaoning Qian, Mingyuan Zhou, Xinjie Fan, 2021, ICLR.

ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables pdf

Mingyuan Zhou, Mingzhang Yin, Yuguang Yue, 2019, ICML.

ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models pdf

Mingyuan Zhou, Mingzhang Yin, Mingyuan Zhou, 2018, ArXiv.

Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression

Quan Zhang, Mingyuan Zhou, Mingyuan Zhou, 2016, J. Mach. Learn. Res..

Adversarially Adaptive Normalization for Single Domain Generalization

Qifei Wang, Boqing Gong, Feng Yang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Dictionary Learning for Noisy and Incomplete Hyperspectral Images

Guillermo Sapiro, Lawrence Carin, Mingyuan Zhou, 2012, SIAM J. Imaging Sci..

Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions

Mingyuan Zhou, Bo Chen, Yulai Cong, 2016, 1607.04751.

Nonparametric Bayesian matrix factorization for assortative networks

Mingyuan Zhou, Mingyuan Zhou, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction pdf

Mingyuan Zhou, Mingyuan Zhou, 2015, AISTATS.

Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations

David M. Blei, Mingyuan Zhou, Hanna M. Wallach, 2016, ICML.

Probabilistic Best Subset Selection via Gradient-Based Optimization

Xiaoning Qian, Mingyuan Zhou, Nhat Ho, 2020, 2006.06448.

Nonparametric Bayesian Negative Binomial Factor Analysis

Mingyuan Zhou, Mingyuan Zhou, 2016, Bayesian Analysis.

Augment-and-Conquer Negative Binomial Processes

Lawrence Carin, Mingyuan Zhou, L. Carin, 2012, NIPS.

Weibull Racing Time-to-event Modeling and Analysis of Online Borrowers' Loan Payoff and Default.

Mingyuan Zhou, Qiang Gao, Mingfeng Lin, 2019 .

Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-varying Covariates

Mingyuan Zhou, Mei-Cheng Wang, Yanxun Xu, 2019, 1911.01827.

Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks

Quan Zhang, Mingyuan Zhou, Mingyuan Zhou, 2018, NeurIPS.

Gamma Process Poisson Factorization for Joint Modeling of Network and Documents

Joydeep Ghosh, Ayan Acharya, Mingyuan Zhou, 2015, ECML/PKDD.

Gradient estimation of information measures in deep learning

Zenglin Xu, Haoli Bai, Lirong He, 2021, Knowl. Based Syst..

Mutual Information Gradient Estimation for Representation Learning pdf

Zenglin Xu, Mingyuan Zhou, Liangjian Wen, 2020, ICLR.

Variational Graph Recurrent Neural Networks

Mingyuan Zhou, K. Narayanan, N. Duffield, 2019, NeurIPS.

Augmentable Gamma Belief Networks

Mingyuan Zhou, Bo Chen, Yulai Cong, 2015, J. Mach. Learn. Res..

Covariate-dependent negative binomial factor analysis of RNA sequencing data

Xiaoning Qian, Mingyuan Zhou, Siamak Zamani Dadaneh, 2018, Bioinform..

Bayesian negative binomial regression for differential expression with confounding factors

Xiaoning Qian, Mingyuan Zhou, Siamak Zamani Dadaneh, 2018, Bioinform..

Differential Expression Analysis of Dynamical Sequencing Count Data with a Gamma Markov Chain

Xiaoning Qian, Sing-Hoi Sze, Ehsan Hajiramezanali, 2018, 1803.02527.

Bayesian gamma-negative binomial modeling of single-cell RNA sequencing data

Xiaoning Qian, Mingyuan Zhou, Sing-Hoi Sze, 2019, BMC Genomics.

Mingyuan Zhou, Yizhe Zhang, Xinjie Fan, 2019, ICLR.

Recurrent Hierarchical Topic-Guided RNN for Language Generation

Mingyuan Zhou, Bo Chen, D. Guo, 2019, ICML.

Bidirectional Convolutional Poisson Gamma Dynamical Systems

Bo Chen, Wenchao Chen, Mingyuan Zhou, 2020, NeurIPS.

Recurrent Hierarchical Topic-Guided Neural Language Models pdf

Bo Chen, Mingyuan Zhou, Ruiying Lu, 2019, ArXiv.

On the Integration of Topic Modeling and Dictionary Learning

Guillermo Sapiro, Lawrence Carin, Mingyuan Zhou, 2011, ICML.

Semi-Implicit Variational Inference pdf

Mingyuan Zhou, Mingzhang Yin, Mingyuan Zhou, 2018, ICML.

Graph Gamma Process Linear Dynamical Systems

Rahi Kalantari, Mingyuan Zhou, Mingyuan Zhou, 2021, AISTATS.

Graph Gamma Process Generalized Linear Dynamical Systems pdf

Mingyuan Zhou, Rahi Kalantari, Mingyuan Zhou, 2020, ArXiv.

Nonparametric Bayesian sparse graph linear dynamical systems

Joydeep Ghosh, Mingyuan Zhou, Rahi Kalantari, 2018, AISTATS.

Truncated Diffusion Probabilistic Models

Mingyuan Zhou, Weizhu Chen, Pengcheng He, 2022, ArXiv.

Partition-Guided GANs

Mingyuan Zhou, Chunyuan Li, A. Sadeghian, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Convex Polytope Trees pdf

Mingyuan Zhou, Mohammadreza Armandpour, Mingyuan Zhou, 2020, ArXiv.

A Prototype-Oriented Framework for Unsupervised Domain Adaptation pdf

Xinjie Fan, Bo Chen, Mingyuan Zhou, 2021, NeurIPS.

Masking: A New Perspective of Noisy Supervision

Ivor W. Tsang, Gang Niu, Masashi Sugiyama, 2018, NeurIPS.

In-Context Learning Unlocked for Diffusion Models

Yifan Jiang, Mingyuan Zhou, Weizhu Chen, 2023, ArXiv.

Bayesian Graph Neural Networks with Adaptive Connection Sampling

Xiaoning Qian, Mingyuan Zhou, Ehsan Hajiramezanali, 2020, ICML.

A Bayesian Nonparametric Approach to Image Super-Resolution

Lawrence Carin, David M. Blei, Mingyuan Zhou, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

Yifan Jiang, Mingyuan Zhou, Weizhu Chen, 2023, ArXiv.

Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection

Mingyuan Zhou, Bo Chen, Liang Dai, 2022, ICML.

Self-supervised Pre-training with Hard Examples Improves Visual Representations pdf

Jianfeng Gao, Xiujun Li, Lei Zhang, 2020, ArXiv.

A Regularized Implicit Policy for Offline Reinforcement Learning

Yihao Feng, Mingyuan Zhou, Huangjie Zheng, 2022, ArXiv.

Semi-Implicit Graph Variational Auto-Encoders

Xiaoning Qian, Mingyuan Zhou, Ehsan Hajiramezanali, 2019, NeurIPS.

Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network

Bo Chen, Dongsheng Wang, Mingyuan Zhou, 2020, NeurIPS.

Negative Binomial Process Count and Mixture Modeling

Lawrence Carin, Mingyuan Zhou, L. Carin, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data

Mingyuan Zhou, Bo Chen, Zhengjue Wang, 2021, IEEE Transactions on Cybernetics.

ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks

Mingyuan Zhou, Mingzhang Yin, Mingyuan Zhou, 2018, ICLR.

Locally Private Bayesian Inference for Count Models pdf

Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach, 2018, ICML.

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

Mingyuan Zhou, Bo Chen, Huangjie Zheng, 2022, ICLR.

Friendly Topic Assistant for Transformer Based Abstractive Summarization

Bo Chen, Mingyuan Zhou, Hao Zhang, 2020, EMNLP.

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

Hao Zhang, Mingyuan Zhou, Bo Chen, 2018, ICLR.

Learning Prototype-oriented Set Representations for Meta-Learning

H. Zha, Mingyuan Zhou, Minghe Zhang, 2021, ICLR.

Learnable Bernoulli Dropout for Bayesian Deep Learning pdf

Xiaoning Qian, Mingyuan Zhou, Shahin Boluki, 2020, AISTATS.

A Dual Markov Chain Topic Model for Dynamic Environments

Joydeep Ghosh, Ayan Acharya, Mingyuan Zhou, 2018, KDD.

Dirichlet belief networks for topic structure learning pdf

Lan Du, He Zhao, Mingyuan Zhou, 2018, NeurIPS.

Deep Poisson gamma dynamical systems

Mingyuan Zhou, Bo Chen, Dandan Guo, 2018, NeurIPS.

Poisson-Gamma dynamical systems

Mingyuan Zhou, Hanna M. Wallach, Aaron Schein, 2016, NIPS.

Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

Joydeep Ghosh, Ayan Acharya, Mingyuan Zhou, 2015, AISTATS.

Demystifying Assumptions in Learning to Discover Novel Classes

Long Lan, Masashi Sugiyama, Tongliang Liu, 2021 .

POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models

Mingyuan Zhou, Pengcheng He, Huangjie Zheng, 2023, ICML.

Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models

Mingyuan Zhou, Bo Chen, Xinyang Liu, 2023, ArXiv.

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network

Zhibin Duan, Bo Chen, Jie Ren, 2021, ICML.

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions

Mingyuan Zhou, Huangjie Zheng, 2020, NeurIPS.

Thompson Sampling via Local Uncertainty

Mingyuan Zhou, Zhendong Wang, 2019, ICML.

Multimodal Poisson Gamma Belief Network

Mingyuan Zhou, Bo Chen, Chaojie Wang, 2018, AAAI.

Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC

Hongwei Liu, Mingyuan Zhou, Bo Chen, 2017, ICML.

A Prototype-Oriented Clustering for Domain Shift with Source Privacy

Mingyuan Zhou, Pengcheng He, Shujian Zhang, 2023, ArXiv.

Bayesian Attention Belief Networks pdf

Xinjie Fan, Bo Chen, Mingyuan Zhou, 2021, ICML.

Bayesian Attention Modules pdf

Bo Chen, Mingyuan Zhou, Xinjie Fan, 2020, NeurIPS.

Semi-supervised learning using adversarial training with good and bad samples

Mingyuan Zhou, William Speier, Corey W. Arnold, 2019, Machine Vision and Applications.

Semi-Implicit Stochastic Recurrent Neural Networks

Mingyuan Zhou, K. Narayanan, N. Duffield, 2019, IEEE International Conference on Acoustics, Speech, and Signal Processing.

Contrastive Conditional Transport for Representation Learning pdf

Hongxia Yang, Jingren Zhou, Ivor Tsang, 2021, ArXiv.

Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data

Xiaoning Qian, Mingyuan Zhou, Ehsan Hajiramezanali, 2018, NeurIPS.

Alignment Attention by Matching Key and Query Distributions pdf

Xinjie Fan, Mingyuan Zhou, Shujian Zhang, 2021, NeurIPS.

Arsm Gradient Estimator for Supervised Learning to Rank

Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian, 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A mixture-density-based tandem optimization network for on-demand inverse design of thin-film high reflectors

Mingyuan Zhou, Kan Yao, Yuebing Zheng, 2021, Nanophotonics.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Michael W. Dusenberry, Benjamin D. Trump, Michael L. Mayo, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Class-Balancing Diffusion Models

Mingyuan Zhou, Ya Zhang, Huangjie Zheng, 2023, arXiv.org.

Truncated Diffusion Probabilistic Models

Mingyuan Zhou, Weizhu Chen, Pengcheng He, 2022, ICLR.

BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment.

Mingyuan Zhou, R. White, Wesley Tansey, 2023, Cell systems.

Contrastive Attraction and Contrastive Repulsion for Representation Learning

I. Tsang, Mingyuan Zhou, Jingren Zhou, 2021, Trans. Mach. Learn. Res..

Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling

Mingyuan Zhou, Tianqi Chen, 2023, ICML.

Convolutional Poisson Gamma Belief Network

Mingyuan Zhou, Bo Chen, Chaojie Wang, 2019, ICML.

ACT: Asymptotic Conditional Transport pdf

Mingyuan Zhou, Huangjie Zheng, Mingyuan Zhou, 2020, ArXiv.

Variational Temporal Deep Generative Model for Radar HRRP Target Recognition

Mingyuan Zhou, Bo Chen, Hongwei Liu, 2020, IEEE Transactions on Signal Processing.

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Jonathan J. Hunt, Mingyuan Zhou, Zhendong Wang, 2022, ICLR.

Diffusion-GAN: Training GANs with Diffusion

Mingyuan Zhou, Weizhu Chen, Pengcheng He, 2022, ICLR.

Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient

Mingyuan Zhou, Bo An, Bo Chen, 2022, NeurIPS.

Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification

Bo Chen, Mingyuan Zhou, Chaojie Wang, 2020, AISTATS.

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification

Mingyuan Zhou, Xinyang Liu, Ruiying Lu, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-varying Covariates

Mingyuan Zhou, Mei-Cheng Wang, Yanxun Xu, 2019, 1911.01827.

Implicit Distributional Reinforcement Learning pdf

Mingyuan Zhou, Zhendong Wang, Yuguang Yue, 2020, NeurIPS.

Lognormal and Gamma Mixed Negative Binomial Regression

David B. Dunson, Lawrence Carin, Mingyuan Zhou, 2012, ICML.

Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012

Lawrence Carin, Lingbo Li, Mingyuan Zhou, 2012, UAI 2012.

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables

Alek Dimitriev, Mingyuan Zhou, Mingyuan Zhou, 2021, ICML.

TopicNet: Semantic Graph-Guided Topic Discovery pdf

Zhibin Duan, Bo Chen, Mingyuan Zhou, 2021, NeurIPS.

Inter and Intra Topic Structure Learning with Word Embeddings

Lan Du, He Zhao, Mingyuan Zhou, 2018, ICML.

Generative Text Convolutional Neural Network for Hierarchical Document Representation Learning

Mingyuan Zhou, Bo Chen, Hao Zhang, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Variational Autoencoders for Sparse and Overdispersed Discrete Data

Lan Du, He Zhao, Mingyuan Zhou, 2019, AISTATS.

CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator pdf

Alek Dimitriev, Mingyuan Zhou, Mingyuan Zhou, 2021, NeurIPS.

Truncated Diffusion Probabilistic Models

Mingyuan Zhou, Weizhu Chen, Pengcheng He, 2022, ICLR.

Deep Topic Models for Multi-label Learning

Ankit Pensia, Mingyuan Zhou, Piyush Rai, 2019, AISTATS.

Negative Binomial Process Count and Mixture Modeling

L. Carin, Mingyuan Zhou, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Jonathan J. Hunt, Mingyuan Zhou, Zhendong Wang, 2022, ICLR.

In-Context Learning Unlocked for Diffusion Models

Yifan Jiang, Mingyuan Zhou, Weizhu Chen, 2023, NeurIPS.

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

Yifan Jiang, Mingyuan Zhou, Weizhu Chen, 2023, NeurIPS.

Switching Poisson Gamma Dynamical Systems

Bo Chen, Yicheng Liu, Wenchao Chen, 2020, IJCAI.

Deep Autoencoding Topic Model With Scalable Hybrid Bayesian Inference

Bo Chen, Hongwei Liu, Mingyuan Zhou, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Variational Hetero-Encoder Randomized Generative Adversarial Networks for Joint Image-Text Modeling

Mingyuan Zhou, Bo Chen, Zhengjue Wang, 2019, ArXiv.

Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning

Mingyuan Zhou, Bo Chen, Yicheng Liu, 2022, IEEE Transactions on Signal Processing.

Probabilistic Margins for Instance Reweighting in Adversarial Training

Masashi Sugiyama, Mingyuan Zhou, Tongliang Liu, 2021, NeurIPS.

Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data

Lan Du, He Zhao, Mingyuan Zhou, 2019, 1905.00616.

Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process

Mingyuan Zhou, Bo Chen, Xinyang Liu, 2023, ICML.

Deep Generative Models of Sparse and Overdispersed Discrete Data

Mingyuan Zhou, Piyush Rai, He Zhao, 2019 .

The Poisson Gamma Belief Network

Mingyuan Zhou, Bo Chen, Yulai Cong, 2015, NIPS.

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

Mingyuan Zhou, Bo Chen, He Zhao, 2022, ICLR.

Prototype-oriented unsupervised anomaly detection for multivariate time series

Mingyuan Zhou, Bo Chen, Long Tian, 2023, ICML.

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions

Mingyuan Zhou, Huangjie Zheng, 2020, NeurIPS.

Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture

Mingyuan Zhou, Yucheng Wang, Xiaoning Qian, 2022, SenSys.

Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models

Mingyuan Zhou, Bo Chen, Xinyang Liu, 2023, 2303.09100.

A Behavior Regularized Implicit Policy for Offline Reinforcement Learning

Yihao Feng, Mingyuan Zhou, Zhendong Wang, 2022, 2202.09673.