Zhou, Mingyuan

137 publications

ICLR 2025 Advancing Graph Generation Through Beta Diffusion Xinyang Liu, Yilin He, Bo Chen, Mingyuan Zhou

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 DRL: Decomposed Representation Learning for Tabular Anomaly Detection Hangting Ye, He Zhao, Wei Fan, Mingyuan Zhou, Dan dan Guo, Yi Chang

TMLR 2025 Diverse Condensed Data Generation via Class Preserving Distribution Matching Dandan Guo, Zhuo Li, He Zhao, Mingyuan Zhou, Hongyuan Zha

ICLR 2025 Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-Negative Decision Layer Xinyue Hu, Zhibin Duan, Bo Chen, Mingyuan Zhou

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

NeurIPS 2025 Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting Ruyi An, Haicheng Huang, Huangjie Zheng, Mingyuan Zhou

NeurIPS 2025 Generative Model Inversion Through the Lens of the Manifold Hypothesis Xiong Peng, Bo Han, Fengfei Yu, Tongliang Liu, Feng Liu, Mingyuan Zhou

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

NeurIPS 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

ICML 2025 OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-Class Anomaly Detection via Adversarial Distillation Yaoxuan Feng, Wenchao Chen, Yuxin Li, Bo Chen, Yubiao Wang, Zixuan Zhao, Hongwei Liu, Mingyuan Zhou

ICML 2025 One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation Zhendong Wang, Max Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng

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

TMLR 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

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

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

NeurIPS 2024 Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning Tianyu Chen, Zhendong Wang, Mingyuan Zhou

TMLR 2024 Hashing with Uncertainty Quantification via Sampling-Based Hypothesis Testing Yucheng Wang, Mingyuan Zhou, Xiaoning Qian

CVPR 2024 Improving Unsupervised Hierarchical Representation with Reinforcement Learning Ruyi An, Yewen Li, Xu He, Pengjie Gu, Mengchen Zhao, Dong Li, Jianye Hao, Chaojie Wang, Bo An, Mingyuan Zhou

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 Long-Tailed Diffusion Models with Oriented Calibration Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang

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

CVPRW 2024 OpenStory: A Large-Scale Open-Domain Dataset for Subject-Driven Visual Storytelling Zilyu Ye, Jinxiu Liu, Jinjin Cao, Zhiyang Chen, Ziwei Xuan, Mingyuan Zhou, Qi Liu, Guo-Jun Qi

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

NeurIPS 2024 Pseudo-Private Data Guided Model Inversion Attacks Xiong Peng, Bo Han, Feng Liu, Tongliang Liu, 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 Switchable Decision: Dynamic Neural Generation Networks Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou

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

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

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

NeurIPS 2023 Beta Diffusion Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng

CVPR 2023 Class-Balancing Diffusion Models Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou, Ya Zhang

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, Mingyuan Zhou

TMLR 2023 Contrastive Attraction and Contrastive Repulsion for Representation Learning Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou

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

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 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, Caiming Xiong, Mingyuan Zhou, Huan Wang

NeurIPS 2023 Few-Shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory Zhibin Duan, Zhiyi Lv, Chaojie Wang, Bo Chen, Bo An, Mingyuan Zhou

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

ICML 2023 Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling Tianqi Chen, 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

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

ICCV 2023 PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification Miaoge Li, Dongsheng Wang, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen, 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

AISTATS 2023 Probabilistic Conformal Prediction Using Conditional Random Samples Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David Blei

ICML 2023 Prototype-Oriented Unsupervised Anomaly Detection for Multivariate Time Series Yuxin Li, Wenchao Chen, Bo Chen, Dongsheng Wang, Long Tian, Mingyuan Zhou

ICLR 2023 Truncated Diffusion Probabilistic Models and Diffusion-Based Adversarial Auto-Encoders Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou

AISTATS 2023 Uncertainty-Aware Unsupervised Video Hashing Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian

JMLR 2023 Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates Quan Zhang, Yanxun Xu, Mei-Cheng Wang, 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 A Variational Edge Partition Model for Supervised Graph Representation Learning Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou

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

NeurIPS 2022 Alleviating "Posterior Collapse'' in Deep Topic Models via Policy Gradient Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Bo An, Mingyuan Zhou

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

NeurIPS 2022 CARD: Classification and Regression Diffusion Models Xizewen Han, Huangjie Zheng, Mingyuan Zhou

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

NeurIPSW 2022 Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou

NeurIPSW 2022 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, Caiming Xiong, Mingyuan Zhou, Huan Wang

NeurIPSW 2022 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, Caiming Xiong, Mingyuan Zhou, Huan Wang

NeurIPS 2022 HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding Yi.shi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou

NeurIPS 2022 Knowledge-Aware Bayesian Deep Topic Model Dongsheng Wang, Yi.shi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou

ICLR 2022 Learning Prototype-Oriented Set Representations for Meta-Learning Dan dan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha

NeurIPS 2022 Learning to Re-Weight Examples with Optimal Transport for Imbalanced Classification Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha

ICLR 2022 Meta Discovery: Learning to Discover Novel Classes Given Very Limited Data Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

ICML 2022 Regularizing a Model-Based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning Shentao Yang, Yihao Feng, Shujian Zhang, Mingyuan Zhou

ICLR 2022 Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings Dongsheng Wang, Dan dan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou

AISTATS 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 Tamir

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

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

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

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

ICML 2021 Bayesian Attention Belief Networks Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou

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

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

NeurIPS 2021 Convex Polytope Trees Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou

NeurIPS 2021 Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions Huangjie Zheng, Mingyuan Zhou

CVPR 2021 Partition-Guided GANs Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li, Mingyuan Zhou

ICCV 2021 Polarimetric Helmholtz Stereopsis Yuqi Ding, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jinwei Ye

NeurIPS 2021 Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

ICML 2021 Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou

NeurIPS 2021 TopicNet: Semantic Graph-Guided Topic Discovery Zhibin Duan, Yi.shi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou

ICLR 2020 Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou

NeurIPS 2020 Bayesian Attention Modules Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou

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

NeurIPS 2020 Bidirectional Convolutional Poisson Gamma Dynamical Systems Wenchao Chen, Chaojie Wang, Bo Chen, Yicheng Liu, Hao Zhang, Mingyuan Zhou

NeurIPS 2020 Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network Chaojie Wang, Hao Zhang, Bo Chen, Dongsheng Wang, Zhengjue Wang, Mingyuan Zhou

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

NeurIPS 2020 Implicit Distributional Reinforcement Learning Yuguang Yue, Zhendong Wang, Mingyuan Zhou

AISTATS 2020 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, Hao Zhang, Zhibin Duan, Mingyuan Zhou, Bo Chen

ICLR 2020 Meta-Learning Without Memorization Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn

ICLR 2020 Mutual Information Gradient Estimation for Representation Learning Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu

UAI 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

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

IJCAI 2020 Switching Poisson Gamma Dynamical Systems Wenchao Chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou

ICML 2020 Thompson Sampling via Local Uncertainty Zhendong Wang, Mingyuan Zhou

AISTATS 2020 Variational Autoencoders for Sparse and Overdispersed Discrete Data He Zhao, Piyush Rai, Lan Du, Wray Buntine, Dinh Phung, Mingyuan Zhou

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

ICLR 2019 ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks Mingzhang Yin, Mingyuan Zhou

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

ICML 2019 Convolutional Poisson Gamma Belief Network Chaojie Wang, Bo Chen, Sucheng Xiao, Mingyuan Zhou

AISTATS 2019 Deep Topic Models for Multi-Label Learning Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai

ICML 2019 Locally Private Bayesian Inference for Count Models Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna Wallach

NeurIPS 2019 Poisson-Randomized Gamma Dynamical Systems Aaron Schein, Scott Linderman, Mingyuan Zhou, David Blei, Hanna Wallach

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

NeurIPS 2019 Variational Graph Recurrent Neural Networks Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian

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 Deep Poisson Gamma Dynamical Systems Dandan Guo, Bo Chen, Hao Zhang, Mingyuan Zhou

NeurIPS 2018 Dirichlet Belief Networks for Topic Structure Learning He Zhao, Lan Du, Wray Buntine, Mingyuan Zhou

ICML 2018 Inter and Intra Topic Structure Learning with Word Embeddings He Zhao, Lan Du, Wray Buntine, Mingyuan Zhou

NeurIPS 2018 Masking: A New Perspective of Noisy Supervision Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor Tsang, Ya Zhang, Masashi Sugiyama

AAAI 2018 Multimodal Poisson Gamma Belief Network Chaojie Wang, Bo Chen, Mingyuan Zhou

NeurIPS 2018 Nonparametric Bayesian Lomax Delegate Racing for Survival Analysis with Competing Risks Quan Zhang, Mingyuan Zhou

AISTATS 2018 Nonparametric Bayesian Sparse Graph Linear Dynamical Systems Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou

NeurIPS 2018 Parsimonious Bayesian Deep Networks Mingyuan Zhou

ICML 2018 Semi-Implicit Variational Inference Mingzhang Yin, Mingyuan Zhou

ICLR 2018 WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou

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

JMLR 2016 Augmentable Gamma Belief Networks Mingyuan Zhou, Yulai Cong, Bo Chen

ICML 2016 Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations Aaron Schein, Mingyuan Zhou, David Blei, Hanna Wallach

NeurIPS 2016 Poisson-Gamma Dynamical Systems Aaron Schein, Hanna Wallach, Mingyuan Zhou

CVPR 2016 Rotational Crossed-Slit Light Field Nianyi Li, Haiting Lin, Bilin Sun, Mingyuan Zhou, Jingyi Yu

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

AISTATS 2015 Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction Mingyuan Zhou

AISTATS 2015 Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou

NeurIPS 2015 The Poisson Gamma Belief Network Mingyuan Zhou, Yulai Cong, Bo Chen

NeurIPS 2014 Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling Mingyuan Zhou

NeurIPS 2012 Augment-and-Conquer Negative Binomial Processes Mingyuan Zhou, Lawrence Carin

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

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

UAI 2012 Nested Dictionary Learning for Hierarchical Organization of Imagery and Text Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin

AISTATS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David Dunson, Lawrence Carin

ICML 2011 On the Integration of Topic Modeling and Dictionary Learning Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin

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