On the relationship of non-parametric methods for coherence function estimation. - Chengshi Zheng; Mingyuan Zhou; Xiaodong Li 002 (Signal Process., 2008)

Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations. - Mingyuan Zhou; Haojun Chen; John W. Paisley; Lu Ren; Guillermo Sapiro; Lawrence Carin (NIPS, 2009)

Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. - John W. Paisley; Mingyuan Zhou; Guillermo Sapiro; Lawrence Carin (ICIP, 2010)

IBM Research TRECVID-2010 Video Copy Detection and Multimedia Event Detection System. - Matthew L. Hill; Gang Hua 001; Apostol Natsev; John R. Smith; Lexing Xie; Bert Huang; Michele Merler; Hua Ouyang; Mingyuan Zhou (TRECVID, 2010)

Joint dictionary learning and topic modeling for image clustering. - Lingbo Li 002; Mingyuan Zhou; Eric Wang; Lawrence Carin (ICASSP, 2011)

Covariate-dependent dictionary learning and sparse coding. - Mingyuan Zhou; Hongxia Yang; Guillermo Sapiro; David B. Dunson; Lawrence Carin (ICASSP, 2011)

On the Integration of Topic Modeling and Dictionary Learning. - Lingbo Li 002; Mingyuan Zhou; Guillermo Sapiro; Lawrence Carin (ICML, 2011)

Dependent Hierarchical Beta Process for Image Interpolation and Denoising. - Mingyuan Zhou; Hongxia Yang; Guillermo Sapiro; David B. Dunson; Lawrence Carin (AISTATS, 2011)

A GPU-based implementation of an enhanced GEP algorithm. - Shuai Shao; Xiyang Liu; Mingyuan Zhou; Jiguo Zhan; Xin Liu; Yanli Chu; Hao Chen (GECCO, 2012)

Online Bayesian dictionary learning for large datasets. - Lingbo Li 002; Jorge G. Silva; Mingyuan Zhou; Lawrence Carin (ICASSP, 2012)

Lognormal and Gamma Mixed Negative Binomial Regression. - Mingyuan Zhou; Lingbo Li 002; David B. Dunson; Lawrence Carin (ICML, 2012)

The contextual focused topic model. - Xu Chen 017; Mingyuan Zhou; Lawrence Carin (KDD, 2012)

Augment-and-Conquer Negative Binomial Processes. - Mingyuan Zhou; Lawrence Carin (NIPS, 2012)

Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. - Lingbo Li 002; XianXing Zhang; Mingyuan Zhou; Lawrence Carin (UAI, 2012)

Beta-Negative Binomial Process and Poisson Factor Analysis. - Mingyuan Zhou; Lauren Hannah; David B. Dunson; Lawrence Carin (AISTATS, 2012)

Dictionary Learning for Noisy and Incomplete Hyperspectral Images. - Zhengming Xing; Mingyuan Zhou; Alexey Castrodad; Guillermo Sapiro; Lawrence Carin (SIAM J. Imaging Sci., 2012)

Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. - Mingyuan Zhou; Haojun Chen; John W. Paisley; Lu Ren; Lingbo Li 002; Zhengming Xing; David B. Dunson; Guillermo Sapiro; Lawrence Carin (IEEE Trans. Image Process., 2012)

Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling. - Mingyuan Zhou (NIPS, 2014)

Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling. - David E. Carlson; Joshua T. Vogelstein; Qisong Wu; Wenzhao Lian; Mingyuan Zhou; Colin R. Stoetzner; Daryl Kipke; Douglas Weber; David B. Dunson; Lawrence Carin (IEEE Trans. Biomed. Eng., 2014)

Hybrid sensing face detection and recognition. - Mingyuan Zhou; Haiting Lin; Jingyi Yu; S. Susan Young (AIPR, 2015)

Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices. - Ayan Acharya; Joydeep Ghosh; Mingyuan Zhou (AISTATS, 2015)

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction. - Mingyuan Zhou (AISTATS, 2015)

Nonparametric Bayesian matrix factorization for assortative networks. - Mingyuan Zhou (EUSIPCO, 2015)

The Poisson Gamma Belief Network. - Mingyuan Zhou; Yulai Cong; Bo Chen 001 (NIPS, 2015)

Gamma Process Poisson Factorization for Joint Modeling of Network and Documents. - Ayan Acharya; Dean Teffer; Jette Henderson; Marcus Tyler; Mingyuan Zhou; Joydeep Ghosh (ECML/PKDD (1), 2015)

A Bayesian Nonparametric Approach to Image Super-Resolution. - Gungor Polatkan; Mingyuan Zhou; Lawrence Carin; David M. Blei; Ingrid Daubechies (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Negative Binomial Process Count and Mixture Modeling. - Mingyuan Zhou; Lawrence Carin (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Rotational Crossed-Slit Light Fields. - Nianyi Li; Haiting Lin; Bilin Sun; Mingyuan Zhou; Jingyi Yu (CVPR, 2016)

Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. - Aaron Schein; Mingyuan Zhou; David M. Blei; Hanna M. Wallach (ICML, 2016)

Poisson-Gamma dynamical systems. - Aaron Schein; Hanna M. Wallach; Mingyuan Zhou (NIPS, 2016)

Augmentable Gamma Belief Networks. - Mingyuan Zhou; Yulai Cong; Bo Chen 001 (J. Mach. Learn. Res., 2016)

Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC. - Yulai Cong; Bo Chen 001; Hongwei Liu 001; Mingyuan Zhou (ICML, 2017)

Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression. - Quan Zhang; Mingyuan Zhou (J. Mach. Learn. Res., 2017)

Multimodal Poisson Gamma Belief Network. - Chaojie Wang 001; Bo Chen 001; Mingyuan Zhou (AAAI, 2018)

Nonparametric Bayesian sparse graph linear dynamical systems. - Rahi Kalantari; Joydeep Ghosh; Mingyuan Zhou (AISTATS, 2018)

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling. - Hao Zhang 050; Bo Chen 001; Dandan Guo; Mingyuan Zhou (ICLR (Poster), 2018)

Semi-Implicit Variational Inference. - Mingzhang Yin; Mingyuan Zhou (ICML, 2018)

Inter and Intra Topic Structure Learning with Word Embeddings. - He Zhao 001; Lan Du 002; Wray L. Buntine; Mingyuan Zhou (ICML, 2018)

A Dual Markov Chain Topic Model for Dynamic Environments. - Ayan Acharya; Joydeep Ghosh; Mingyuan Zhou (KDD, 2018)

Deep Poisson gamma dynamical systems. - Dandan Guo; Bo Chen 001; Hao Zhang 050; Mingyuan Zhou (NeurIPS, 2018)

Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. - Ehsan Hajiramezanali; Siamak Zamani Dadaneh; Alireza Karbalayghareh; Mingyuan Zhou; Xiaoning Qian (NeurIPS, 2018)

Masking: A New Perspective of Noisy Supervision. - Bo Han 003; Jiangchao Yao; Gang Niu 001; Mingyuan Zhou; Ivor W. Tsang; Ya Zhang 002; Masashi Sugiyama (NeurIPS, 2018)

Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks. - Quan Zhang; Mingyuan Zhou (NeurIPS, 2018)

Dirichlet belief networks for topic structure learning. - He Zhao 001; Lan Du 002; Wray L. Buntine; Mingyuan Zhou (NeurIPS, 2018)

Parsimonious Bayesian deep networks. - Mingyuan Zhou (NeurIPS, 2018)

Covariate-dependent negative binomial factor analysis of RNA sequencing data. - Siamak Zamani Dadaneh; Mingyuan Zhou; Xiaoning Qian (Bioinform., 2018)

Bayesian negative binomial regression for differential expression with confounding factors. - Siamak Zamani Dadaneh; Mingyuan Zhou; Xiaoning Qian (Bioinform., 2018)

Locally Private Bayesian Inference for Count Models. - Aaron Schein; Zhiwei Steven Wu; Mingyuan Zhou; Hanna M. Wallach (CoRR, 2018)

ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models. - Mingzhang Yin; Mingyuan Zhou (CoRR, 2018)

Deep Topic Models for Multi-label Learning. - Rajat Panda; Ankit Pensia; Nikhil Mehta 002; Mingyuan Zhou; Piyush Rai (AISTATS, 2019)

ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks. - Mingzhang Yin; Mingyuan Zhou (ICLR (Poster), 2019)

Locally Private Bayesian Inference for Count Models. - Aaron Schein; Zhiwei Steven Wu; Alexandra Schofield; Mingyuan Zhou; Hanna M. Wallach (ICML, 2019)

Convolutional Poisson Gamma Belief Network. - Chaojie Wang 001; Bo Chen 001; Sucheng Xiao; Mingyuan Zhou (ICML, 2019)

ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. - Mingzhang Yin; Yuguang Yue; Mingyuan Zhou (ICML, 2019)

Variational Graph Recurrent Neural Networks. - Ehsan Hajiramezanali; Arman Hasanzadeh; Krishna R. Narayanan; Nick Duffield; Mingyuan Zhou; Xiaoning Qian (NeurIPS, 2019)

Semi-Implicit Graph Variational Auto-Encoders. - Arman Hasanzadeh; Ehsan Hajiramezanali; Krishna R. Narayanan; Nick Duffield; Mingyuan Zhou; Xiaoning Qian (NeurIPS, 2019)

Poisson-Randomized Gamma Dynamical Systems. - Aaron Schein; Scott W. Linderman; Mingyuan Zhou; David M. Blei; Hanna M. Wallach (NeurIPS, 2019)

Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy. - Yunhao Tang; Mingzhang Yin; Mingyuan Zhou (CoRR, 2019)

Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field. - Mingyuan Zhou; Yu Ji 001; Yuqi Ding; Jinwei Ye; S. Susan Young; Jingyi Yu (CoRR, 2019)

Variational Autoencoders for Sparse and Overdispersed Discrete Data. - He Zhao 001; Piyush Rai; Lan Du 002; Wray L. Buntine; Mingyuan Zhou (CoRR, 2019)

Variational Hetero-Encoder Randomized Generative Adversarial Networks for Joint Image-Text Modeling. - Hao Zhang 050; Bo Chen 001; Long Tian; Zhengjue Wang; Mingyuan Zhou (CoRR, 2019)

Semi-Implicit Generative Model. - Mingzhang Yin; Mingyuan Zhou (CoRR, 2019)

Recurrent Hierarchical Topic-Guided Neural Language Models. - Dandan Guo; Bo Chen 001; Ruiying Lu; Mingyuan Zhou (CoRR, 2019)

Content Aware Image Pre-Compensation. - Jinwei Ye; Yu Ji 001; Mingyuan Zhou; Sing Bing Kang; Jingyi Yu (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Learnable Bernoulli Dropout for Bayesian Deep Learning. - Shahin Boluki; Randy Ardywibowo; Siamak Zamani Dadaneh; Mingyuan Zhou; Xiaoning Qian (AISTATS, 2020)

Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification. - Zhengjue Wang; Chaojie Wang 001; Hao Zhang 050; Zhibin Duan; Mingyuan Zhou; Bo Chen 001 (AISTATS, 2020)

Discrete Action On-Policy Learning with Action-Value Critic. - Yuguang Yue; Yunhao Tang; Mingzhang Yin; Mingyuan Zhou (AISTATS, 2020)

Variational Autoencoders for Sparse and Overdispersed Discrete Data. - He Zhao 001; Piyush Rai; Lan Du 002; Wray L. Buntine; Dinh Phung 001; Mingyuan Zhou (AISTATS, 2020)

Friendly Topic Assistant for Transformer Based Abstractive Summarization. - Zhengjue Wang; Zhibin Duan; Hao Zhang 050; Chaojie Wang 001; Long Tian; Bo Chen 001; Mingyuan Zhou (EMNLP (1), 2020)

Arsm Gradient Estimator for Supervised Learning to Rank. - Siamak Zamani Dadaneh; Shahin Boluki; Mingyuan Zhou; Xiaoning Qian (ICASSP, 2020)

Semi-Implicit Stochastic Recurrent Neural Networks. - Ehsan Hajiramezanali; Arman Hasanzadeh; Nick Duffield; Krishna Narayanan 001; Mingyuan Zhou; Xiaoning Qian (ICASSP, 2020)

3D Face Reconstruction using Color Photometric Stereo with Uncalibrated Near Point Lights. - Zhang Chen; Yu Ji 001; Mingyuan Zhou; Sing Bing Kang; Jingyi Yu (ICCP, 2020)

Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling. - Hao Zhang 050; Bo Chen 001; Long Tian; Zhengjue Wang; Mingyuan Zhou (ICLR, 2020)

Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation. - Xinjie Fan; Yizhe Zhang 002; Zhendong Wang; Mingyuan Zhou (ICLR, 2020)

Mutual Information Gradient Estimation for Representation Learning. - Liangjian Wen; Yiji Zhou; Lirong He; Mingyuan Zhou; Zenglin Xu (ICLR, 2020)

Meta-Learning without Memorization. - Mingzhang Yin; George Tucker; Mingyuan Zhou; Sergey Levine; Chelsea Finn (ICLR, 2020)

Recurrent Hierarchical Topic-Guided RNN for Language Generation. - Dandan Guo; Bo Chen 001; Ruiying Lu; Mingyuan Zhou (ICML, 2020)

Bayesian Graph Neural Networks with Adaptive Connection Sampling. - Arman Hasanzadeh; Ehsan Hajiramezanali; Shahin Boluki; Mingyuan Zhou; Nick Duffield; Krishna Narayanan 001; Xiaoning Qian (ICML, 2020)

Thompson Sampling via Local Uncertainty. - Zhendong Wang; Mingyuan Zhou (ICML, 2020)

Switching Poisson Gamma Dynamical Systems. - Wenchao Chen; Bo Chen 001; Yicheng Liu; Qianru Zhao; Mingyuan Zhou (IJCAI, 2020)

Bidirectional Convolutional Poisson Gamma Dynamical Systems. - Wenchao Chen; Chaojie Wang 001; Bo Chen 001; Yicheng Liu; Hao Zhang 050; Mingyuan Zhou (NeurIPS, 2020)

Bayesian Attention Modules. - Xinjie Fan; Shujian Zhang; Bo Chen 001; Mingyuan Zhou (NeurIPS, 2020)

Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network. - Chaojie Wang 001; Hao Zhang 050; Bo Chen 001; Dongsheng Wang 003; Zhengjue Wang; Mingyuan Zhou (NeurIPS, 2020)

Implicit Distributional Reinforcement Learning. - Yuguang Yue; Zhendong Wang; Mingyuan Zhou (NeurIPS, 2020)

Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. - Siamak Zamani Dadaneh; Shahin Boluki; Mingzhang Yin; Mingyuan Zhou; Xiaoning Qian (UAI, 2020)

Graph Gamma Process Generalized Linear Dynamical Systems. - Rahi Kalantari; Mingyuan Zhou (CoRR, 2020)

MCMC-Interactive Variational Inference. - Quan Zhang; Huangjie Zheng; Mingyuan Zhou (CoRR, 2020)

Convex Polytope Trees. - Mohammadreza Armandpour; Mingyuan Zhou (CoRR, 2020)

Self-supervised Pre-training with Hard Examples Improves Visual Representations. - Chunyuan Li; Xiujun Li; Lei Zhang 001; Baolin Peng; Mingyuan Zhou; Jianfeng Gao 001 (CoRR, 2020)

ACT: Asymptotic Conditional Transport. - Huangjie Zheng; Mingyuan Zhou (CoRR, 2020)

Semi-supervised learning using adversarial training with good and bad samples. - Wenyuan Li 001; Zichen Wang; Yuguang Yue; Jiayun Li; William Speier; Mingyuan Zhou; Corey W. Arnold (Mach. Vis. Appl., 2020)

Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field. - Mingyuan Zhou; Yuqi Ding; Yu Ji 001; S. Susan Young; Jingyi Yu; Jinwei Ye (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Variational Temporal Deep Generative Model for Radar HRRP Target Recognition. - Dandan Guo; Bo Chen 001; Wenchao Chen; Chaojie Wang 001; Hongwei Liu 001; Mingyuan Zhou (IEEE Trans. Signal Process., 2020)

EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering. - Zhibin Duan; Hao Zhang 050; Chaojie Wang 001; Zhengjue Wang; Bo Chen 001; Mingyuan Zhou (ACL/IJCNLP (1), 2021)

Graph Gamma Process Linear Dynamical Systems. - Rahi Kalantari; Mingyuan Zhou (AISTATS, 2021)

Hyperbolic graph embedding with enhanced semi-implicit variational inference. - Ali Lotfi-Rezaabad; Rahi Kalantari; Sriram Vishwanath; Mingyuan Zhou; Jonathan I. Tamir (AISTATS, 2021)

Partition-Guided GANs. - Mohammadreza Armandpour; Ali Sadeghian; Chunyuan Li; Mingyuan Zhou (CVPR, 2021)

Adversarially Adaptive Normalization for Single Domain Generalization. - Xinjie Fan; Qifei Wang; Junjie Ke; Feng Yang; Boqing Gong; Mingyuan Zhou (CVPR, 2021)

Polarimetric Helmholtz Stereopsis. - Yuqi Ding; Yu Ji 001; Mingyuan Zhou; Sing Bing Kang; Jinwei Ye (ICCV, 2021)

Contextual Dropout: An Efficient Sample-Dependent Dropout Module. - Xinjie Fan; Shujian Zhang; Korawat Tanwisuth; Xiaoning Qian; Mingyuan Zhou (ICLR, 2021)

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables. - Aleksandar Dimitriev; Mingyuan Zhou (ICML, 2021)

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network. - Zhibin Duan; Dongsheng Wang 003; Bo Chen 001; Chaojie Wang 001; Wenchao Chen; Yewen Li; Jie Ren; Mingyuan Zhou (ICML, 2021)

Bayesian Attention Belief Networks. - Shujian Zhang; Xinjie Fan; Bo Chen 001; Mingyuan Zhou (ICML, 2021)

Convex Polytope Trees and its Application to VAE. - Mohammadreza Armandpour; Ali Sadeghian; Mingyuan Zhou (NeurIPS, 2021)

CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator. - Alek Dimitriev; Mingyuan Zhou (NeurIPS, 2021)

TopicNet: Semantic Graph-Guided Topic Discovery. - Zhibin Duan; Yishi Xu; Bo Chen 001; Dongsheng Wang 003; Chaojie Wang 001; Mingyuan Zhou (NeurIPS, 2021)

A Prototype-Oriented Framework for Unsupervised Domain Adaptation. - Korawat Tanwisuth; Xinjie Fan; Huangjie Zheng; Shujian Zhang; Hao Zhang 050; Bo Chen 001; Mingyuan Zhou (NeurIPS, 2021)

Probabilistic Margins for Instance Reweighting in Adversarial Training. - Qizhou Wang; Feng Liu 003; Bo Han 003; Tongliang Liu; Chen Gong 002; Gang Niu 001; Mingyuan Zhou; Masashi Sugiyama (NeurIPS, 2021)

Alignment Attention by Matching Key and Query Distributions. - Shujian Zhang; Xinjie Fan; Huangjie Zheng; Korawat Tanwisuth; Mingyuan Zhou (NeurIPS, 2021)

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions. - Huangjie Zheng; Mingyuan Zhou (NeurIPS, 2021)

Contrastive Conditional Transport for Representation Learning. - Huangjie Zheng; Xu Chen 026; Jiangchao Yao; Hongxia Yang; Chunyuan Li; Ya Zhang 002; Hao Zhang 050; Ivor W. Tsang; Jingren Zhou 001; Mingyuan Zhou (CoRR, 2021)

Bayesian Graph Contrastive Learning. - Arman Hasanzadeh; Mohammadreza Armandpour; Ehsan Hajiramezanali; Mingyuan Zhou; Nick Duffield; Krishna Narayanan 001 (CoRR, 2021)

Gradient estimation of information measures in deep learning. - Liangjian Wen; Haoli Bai; Lirong He; Yiji Zhou; Mingyuan Zhou; Zenglin Xu (Knowl. Based Syst., 2021)

Structure From Motion on XSlit Cameras. - Wei Yang 034; Yingliang Zhang; Jinwei Ye; Yu Ji 001; Zhong Li; Mingyuan Zhou; Jingyi Yu (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Deep Autoencoding Topic Model With Scalable Hybrid Bayesian Inference. - Hao Zhang 050; Bo Chen 001; Yulai Cong; Dandan Guo; Hongwei Liu 001; Mingyuan Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. - Dongsheng Wang 003; Dandan Guo; He Zhao 001; Huangjie Zheng; Korawat Tanwisuth; Bo Chen 001; Mingyuan Zhou (ICLR, 2022)

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. - Haoang Chi; Feng Liu 003; Wenjing Yang 002; Long Lan; Tongliang Liu; Bo Han 003; Gang Niu 001; Mingyuan Zhou; Masashi Sugiyama (ICLR, 2022)

Learning Prototype-oriented Set Representations for Meta-Learning. - Dandan Guo; Long Tian; Minghe Zhang; Mingyuan Zhou; Hongyuan Zha (ICLR, 2022)

Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection. - Wenchao Chen; Long Tian; Bo Chen 001; Liang Dai; Zhibin Duan; Mingyuan Zhou (ICML, 2022)

Bayesian Deep Embedding Topic Meta-Learner. - Zhibin Duan; Yishi Xu; Jianqiao Sun; Bo Chen 001; Wenchao Chen; Chaojie Wang 001; Mingyuan Zhou (ICML, 2022)

Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning. - Shentao Yang; Yihao Feng; Shujian Zhang; Mingyuan Zhou (ICML, 2022)

ALLSH: Active Learning Guided by Local Sensitivity and Hardness. - Shujian Zhang; Chengyue Gong; Xingchao Liu; Pengcheng He; Weizhu Chen; Mingyuan Zhou (NAACL-HLT (Findings), 2022)

Knowledge-Aware Bayesian Deep Topic Model. - Dongsheng Wang 003; Yishi Xu; Miaoge Li; Zhibin Duan; Chaojie Wang 001; Bo Chen 001; Mingyuan Zhou (NeurIPS, 2022)

Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. - Dandan Guo; Zhuo Li; Meixi Zheng; He Zhao 001; Mingyuan Zhou; Hongyuan Zha (NeurIPS, 2022)

Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. - Dandan Guo; Long Tian; He Zhao 001; Mingyuan Zhou; Hongyuan Zha (NeurIPS, 2022)

CARD: Classification and Regression Diffusion Models. - Xizewen Han; Huangjie Zheng; Mingyuan Zhou (NeurIPS, 2022)

A Variational Edge Partition Model for Supervised Graph Representation Learning. - Yilin He; Chaojie Wang 001; Hao Zhang 050; Bo Chen 001; Mingyuan Zhou (NeurIPS, 2022)

Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient. - Yewen Li; Chaojie Wang 001; Zhibin Duan; Dongsheng Wang 003; Bo Chen 001; Bo An 001; Mingyuan Zhou (NeurIPS, 2022)

HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding. - Yishi Xu; Dongsheng Wang 003; Bo Chen 001; Ruiying Lu; Zhibin Duan; Mingyuan Zhou (NeurIPS, 2022)

A Unified Framework for Alternating Offline Model Training and Policy Learning. - Shentao Yang; Shujian Zhang; Yihao Feng; Mingyuan Zhou (NeurIPS, 2022)

Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. - Yucheng Wang; Mengmeng Gu; Mingyuan Zhou; Xiaoning Qian (SenSys, 2022)

Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (CoRR, 2022)

Truncated Diffusion Probabilistic Models. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (CoRR, 2022)

A Regularized Implicit Policy for Offline Reinforcement Learning. - Shentao Yang; Zhendong Wang; Huangjie Zheng; Yihao Feng; Mingyuan Zhou (CoRR, 2022)

Ordinal Graph Gamma Belief Network for Social Recommender Systems. - Dongsheng Wang 003; Chaojie Wang 001; Bo Chen 001; Mingyuan Zhou (CoRR, 2022)

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning. - Dandan Guo; Ruiying Lu; Bo Chen 001; Zequn Zeng; Mingyuan Zhou (Int. J. Comput. Vis., 2022)

Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data. - Chaojie Wang 001; Bo Chen 001; Sucheng Xiao; Zhengjue Wang; Hao Zhang 050; Penghui Wang; Ning Han; Mingyuan Zhou (IEEE Trans. Cybern., 2022)

Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning. - Wenchao Chen; Bo Chen 001; Yicheng Liu; Chaojie Wang 001; Xiaojun Peng; Hongwei Liu 001; Mingyuan Zhou (IEEE Trans. Signal Process., 2022)

Probabilistic Conformal Prediction Using Conditional Random Samples. - Zhendong Wang; Ruijiang Gao; Mingzhang Yin; Mingyuan Zhou; David M. Blei (AISTATS, 2023)

Uncertainty-aware Unsupervised Video Hashing. - Yucheng Wang; Mingyuan Zhou; Yu Sun 004; Xiaoning Qian (AISTATS, 2023)

Class-Balancing Diffusion Models. - Yiming Qin; Huangjie Zheng; Jiangchao Yao; Mingyuan Zhou; Ya Zhang 002 (CVPR, 2023)

DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration. - Zhixin Wang; Ziying Zhang; Xiaoyun Zhang 001; Huangjie Zheng; Mingyuan Zhou; Ya Zhang 002; Yanfeng Wang 001 (CVPR, 2023)

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification. - Miaoge Li; Dongsheng Wang 003; Xinyang Liu; Zequn Zeng; Ruiying Lu; Bo Chen 001; Mingyuan Zhou (ICCV, 2023)

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems. - Yihao Feng; Shentao Yang; Shujian Zhang; Jianguo Zhang 005; Caiming Xiong; Mingyuan Zhou; Huan Wang 014 (ICLR, 2023)

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning. - Zhendong Wang; Jonathan J. Hunt; Mingyuan Zhou (ICLR, 2023)

Diffusion-GAN: Training GANs with Diffusion. - Zhendong Wang; Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (ICLR, 2023)

Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (ICLR, 2023)

Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. - Tianqi Chen; Mingyuan Zhou (ICML, 2023)

Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process. - Zhibin Duan; Xinyang Liu; Yudi Su; Yishi Xu; Bo Chen 001; Mingyuan Zhou (ICML, 2023)

Prototype-oriented unsupervised anomaly detection for multivariate time series. - Yuxin Li 003; Wenchao Chen; Bo Chen 001; Dongsheng Wang 003; Long Tian; Mingyuan Zhou (ICML, 2023)

POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models. - Korawat Tanwisuth; Shujian Zhang; Huangjie Zheng; Pengcheng He; Mingyuan Zhou (ICML, 2023)

Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory. - Zhibin Duan; Zhiyi Lv; Chaojie Wang 001; Bo Chen 001; Bo An 001; Mingyuan Zhou (NeurIPS, 2023)

In-Context Learning Unlocked for Diffusion Models. - Zhendong Wang; Yifan Jiang 001; Yadong Lu; Yelong Shen; Pengcheng He; Weizhu Chen; Zhangyang (Atlas) Wang; Mingyuan Zhou (NeurIPS, 2023)

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. - Zhendong Wang; Yifan Jiang 001; Huangjie Zheng; Peihao Wang; Pengcheng He; Zhangyang Wang; Weizhu Chen; Mingyuan Zhou (NeurIPS, 2023)

Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes. - Yishi Xu; Jianqiao Sun; Yudi Su; Xinyang Liu; Zhibin Duan; Bo Chen 001; Mingyuan Zhou (NeurIPS, 2023)

Preference-grounded Token-level Guidance for Language Model Fine-tuning. - Shentao Yang; Shujian Zhang; Congying Xia; Yihao Feng; Caiming Xiong; Mingyuan Zhou (NeurIPS, 2023)

Beta Diffusion. - Mingyuan Zhou; Tianqi Chen; Zhendong Wang; Huangjie Zheng (NeurIPS, 2023)

Generative-Contrastive Learning for Self-Supervised Latent Representations of 3D Shapes from Multi-Modal Euclidean Input. - Chengzhi Wu; Julius Pfrommer; Mingyuan Zhou; Jürgen Beyerer (CoRR, 2023)

A Prototype-Oriented Clustering for Domain Shift with Source Privacy. - Korawat Tanwisuth; Shujian Zhang; Pengcheng He; Mingyuan Zhou (CoRR, 2023)

Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models. - Xinyang Liu; Dongsheng Wang 003; Miaoge Li; Zhibin Duan; Yishi Xu; Bo Chen 001; Mingyuan Zhou (CoRR, 2023)

Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond. - Mohammadreza Armandpour; Ali Sadeghian; Huangjie Zheng; Amir Sadeghian; Mingyuan Zhou (CoRR, 2023)

AutoML-GPT: Automatic Machine Learning with GPT. - Shujian Zhang; Chengyue Gong; Lemeng Wu; Xingchao Liu; Mingyuan Zhou (CoRR, 2023)

Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts. - Tianqi Chen; Yongfei Liu; Zhendong Wang; Jianbo Yuan; Quanzeng You; Hongxia Yang; Mingyuan Zhou (CoRR, 2023)

Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates. - Quan Zhang; Yanxun Xu; Mei-Cheng Wang; Mingyuan Zhou (J. Mach. Learn. Res., 2023)

Contrastive Attraction and Contrastive Repulsion for Representation Learning. - Huangjie Zheng; Xu Chen 026; Jiangchao Yao; Hongxia Yang; Chunyuan Li; Ya Zhang 002; Hao Zhang 050; Ivor W. Tsang; Jingren Zhou 001; Mingyuan Zhou (Trans. Mach. Learn. Res., 2023)

Generative Text Convolutional Neural Network for Hierarchical Document Representation Learning. - Chaojie Wang 001; Bo Chen 001; Zhibin Duan; Wenchao Chen; Hao Zhang 050; Mingyuan Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Learning Hierarchical Document Graphs From Multilevel Sentence Relations. - Hao Zhang 050; Chaojie Wang 001; Zhengjue Wang; Zhibin Duan; Bo Chen 001; Mingyuan Zhou; Ricardo Henao; Lawrence Carin (IEEE Trans. Neural Networks Learn. Syst., 2023)

Improving Unsupervised Hierarchical Representation With Reinforcement Learning. - Ruyi An; Yewen Li; Xu He; Pengjie Gu; Mengchen Zhao; Dong Li 016; Jianye Hao; Chaojie Wang 001; Bo An 001; Mingyuan Zhou (CVPR, 2024)

OmniMotionGPT: Animal Motion Generation with Limited Data. - Zhangsihao Yang; Mingyuan Zhou; Mengyi Shan; Bingbing Wen; Ziwei Xuan; Mitch Hill; Junjie Bai; Guo-Jun Qi; Yalin Wang 001 (CVPR, 2024)

OpenStory: A Large-Scale Open-Domain Dataset for Subject-Driven Visual Storytelling. - Zilyu Ye; Jinxiu Liu; Jinjin Cao; Zhiyang Chen 002; Ziwei Xuan; Mingyuan Zhou; Qi Liu 005; Guo-Jun Qi (CVPR Workshops, 2024)

UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures. - Mingyuan Zhou; Rakib Hyder; Ziwei Xuan; Guojun Qi (CVPR, 2024)

Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting. - Yuxin Li 003; Wenchao Chen; Xinyue Hu; Bo Chen 001; Baolin Sun; Mingyuan Zhou (ICLR, 2024)

Long-tailed Diffusion Models with Oriented Calibration. - Tianjiao Zhang; Huangjie Zheng; Jiangchao Yao; Xiangfeng Wang; Mingyuan Zhou; Ya Zhang 002; Yanfeng Wang 001 (ICLR, 2024)

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling. - Huangjie Zheng; Zhendong Wang; Jianbo Yuan; Guanghan Ning; Pengcheng He; Quanzeng You; Hongxia Yang; Mingyuan Zhou (ICLR, 2024)

Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection. - Yuxin Li 003; Yaoxuan Feng; Bo Chen 001; Wenchao Chen; Yubiao Wang; Xinyue Hu; Baolin Sun; Chunhui Qu; Mingyuan Zhou (ICML, 2024)

A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. - Shentao Yang; Tianqi Chen; Mingyuan Zhou (ICML, 2024)

Switchable Decision: Dynamic Neural Generation Networks. - Shujian Zhang; Korawat Tanwisuth; Chengyue Gong; Pengcheng He; Mingyuan Zhou (ICML, 2024)

Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. - Mingyuan Zhou; Huangjie Zheng; Zhendong Wang; Mingzhang Yin; Hai Huang (ICML, 2024)

Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning. - Tianyu Chen; Zhendong Wang; Mingyuan Zhou (NeurIPS, 2024)

Pseudo-Private Data Guided Model Inversion Attacks. - Xiong Peng; Bo Han 003; Feng Liu 003; Tongliang Liu; Mingyuan Zhou (NeurIPS, 2024)

Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models. - Xinyang Liu; Dongsheng Wang 003; Bowei Fang; Miaoge Li; Yishi Xu; Zhibin Duan; Bo Chen 001; Mingyuan Zhou (UAI, 2024)

Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts. - Yueqin Yin; Zhendong Wang; Yi Gu; Hai Huang; Weizhu Chen; Mingyuan Zhou (CoRR, 2024)

Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization. - Xuxi Chen; Zhendong Wang; Daouda Sow; Junjie Yang; Tianlong Chen 001; Yingbin Liang; Mingyuan Zhou; Zhangyang Wang (CoRR, 2024)

Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment. - Yueqin Yin; Zhendong Wang; Yujia Xie; Weizhu Chen; Mingyuan Zhou (CoRR, 2024)

Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation. - Mingyuan Zhou; Zhendong Wang; Huangjie Zheng; Hai Huang (CoRR, 2024)

Diffusion Boosted Trees. - Xizewen Han; Mingyuan Zhou (CoRR, 2024)

Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization. - Yi Gu; Zhendong Wang; Yueqin Yin; Yujia Xie; Mingyuan Zhou (CoRR, 2024)

Contrastive Factor Analysis. - Zhibin Duan; Tiansheng Wen; Yifei Wang; Chen Zhu; Bo Chen 001; Mingyuan Zhou (CoRR, 2024)

A Non-negative VAE:the Generalized Gamma Belief Network. - Zhibin Duan; Tiansheng Wen; Muyao Wang; Bo Chen 001; Mingyuan Zhou (CoRR, 2024)

Openstory++: A Large-scale Dataset and Benchmark for Instance-aware Open-domain Visual Storytelling. - Zilyu Ye; Jinxiu Liu; Ruotian Peng; Jinjin Cao; Zhiyang Chen 002; Yiyang Zhang; Ziwei Xuan; Mingyuan Zhou; Xiaoqian Shen; Mohamed Elhoseiny; Qi Liu 005; Guo-Jun Qi (CoRR, 2024)

Disentangled Generative Graph Representation Learning. - Xinyue Hu; Zhibin Duan; Xinyang Liu; Yuxin Li 003; Bo Chen 001; Mingyuan Zhou (CoRR, 2024)

Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks. - Chaojie Wang 001; Xinyang Liu; Dongsheng Wang 003; Hao Zhang 050; Bo Chen 001; Mingyuan Zhou (CoRR, 2024)

Parameter estimation of structural dynamics with neural operators enabled surrogate modeling. - Mingyuan Zhou; Haoze Song; Wenjing Ye; Wei Wang; Zhilu Lai (CoRR, 2024)

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation. - Zhendong Wang; Zhaoshuo Li; Ajay Mandlekar; Zhenjia Xu; Jiaojiao Fan; Yashraj S. Narang; Linxi Fan; Yuke Zhu; Yogesh Balaji; Mingyuan Zhou; Ming-Yu Liu 001; Yu Zeng 001 (CoRR, 2024)

Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data. - Mingyuan Zhou; Xudong Jian; Ye Xia 003; Zhilu Lai (CoRR, 2024)

Enhancing and Accelerating Diffusion-Based Inverse Problem Solving through Measurements Optimization. - Tianyu Chen; Zhendong Wang; Mingyuan Zhou (CoRR, 2024)

Polarimetric Helmholtz Stereopsis. - Yuqi Ding; Yu Ji 001; Zhang Chen; Mingyuan Zhou; Sing Bing Kang; Jinwei Ye (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Hierarchical Topic-Aware Contextualized Transformers. - Ruiying Lu; Bo Chen 001; Dandan Guo; Dongsheng Wang 003; Mingyuan Zhou (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

Hashing with Uncertainty Quantification via Sampling-based Hypothesis Testing. - Yucheng Wang; Mingyuan Zhou; Xiaoning Qian (Trans. Mach. Learn. Res., 2024)

Self-Supervised Generative-Contrastive Learning of Multi-Modal Euclidean Input for 3D Shape Latent Representations: A Dynamic Switching Approach. - Chengzhi Wu; Julius Pfrommer; Mingyuan Zhou; Jürgen Beyerer (IEEE Trans. Multim., 2024)

KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding. - Zhangchen Xu; Yang Liu; Yueqin Yin; Mingyuan Zhou; Radha Poovendran (ACL (Findings), 2025)

FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors. - Changlong Shi; He Zhao 001; Bingjie Zhang 009; Mingyuan Zhou; Dandan Guo; Yi Chang 001 (CVPR, 2025)

Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models. - Tianqi Chen; Shujian Zhang; Mingyuan Zhou (ICLR, 2025)

Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer. - Xinyue Hu; Zhibin Duan; Bo Chen; Mingyuan Zhou (ICLR, 2025)

Advancing Graph Generation through Beta Diffusion. - Xinyang Liu; Yilin He; Bo Chen; Mingyuan Zhou (ICLR, 2025)

DRL: Decomposed Representation Learning for Tabular Anomaly Detection. - Hangting Ye; He Zhao 001; Wei Fan 010; Mingyuan Zhou; Dandan Guo; Yi Chang 001 (ICLR, 2025)

Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation. - Mingyuan Zhou; Zhendong Wang; Huangjie Zheng; Hai Huang (ICLR, 2025)

Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step. - Mingyuan Zhou; Huangjie Zheng; Yi Gu; Zhendong Wang; Hai Huang (ICLR, 2025)

Diverse Condensed Data Generation via Class Preserving Distribution Matching. - Dandan Guo; Zhuo Li; He Zhao 001; Mingyuan Zhou; Hongyuan Zha (Trans. Mach. Learn. Res., 2025)

Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model. - Yueqin Yin; Shentao Yang; Yujia Xie; Ziyi Yang; Yuting Sun; Hany Hassan Awadalla; Weizhu Chen; Mingyuan Zhou (CoRR, 2025)

Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation. - Tianyu Chen; Yasi Zhang; Zhendong Wang; Ying Nian Wu; Oscar Leong; Mingyuan Zhou (CoRR, 2025)

A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation. - Xinran Song; Tianyu Chen; Mingyuan Zhou (CoRR, 2025)

Few-Step Diffusion via Score identity Distillation. - Mingyuan Zhou; Yi Gu; Zhendong Wang (CoRR, 2025)

Restoration Score Distillation: From Corrupted Diffusion Pretraining to One-Step High-Quality Generation. - Yasi Zhang; Tianyu Chen; Zhendong Wang; Ying Nian Wu; Mingyuan Zhou; Oscar Leong (CoRR, 2025)

InfLVG: Reinforce Inference-Time Consistent Long Video Generation with GRPO. - Xueji Fang; Liyuan Ma; Zhiyang Chen 002; Mingyuan Zhou; Guo-Jun Qi (CoRR, 2025)

Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power. - Tingpeng Zhang; Xuzhang Peng; Mingyuan Zhou; Guobiao Hu; Zhilu Lai (CoRR, 2025)

Enhancing Uncertainty Estimation and Interpretability via Bayesian Non-negative Decision Layer. - Xinyue Hu; Zhibin Duan; Bo Chen 001; Mingyuan Zhou (CoRR, 2025)

DLM-One: Diffusion Language Models for One-Step Sequence Generation. - Tianqi Chen; Shujian Zhang; Mingyuan Zhou (CoRR, 2025)

Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay. - Yifan Sun; Jingyan Shen; Yibin Wang; Tianyu Chen; Zhendong Wang; Mingyuan Zhou; Huan Zhang (CoRR, 2025)

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion. - Xun Huang; Zhengqi Li; Guande He; Mingyuan Zhou; Eli Shechtman (CoRR, 2025)

Controllable diffusion-based generation for multi-channel biological data. - Haoran Zhang; Mingyuan Zhou; Wesley Tansey (CoRR, 2025)