| 2026 | ACL | ContextCheck: Sentence-Level Faithfulness Verification with Context-Aware Disambiguation. | Yueqin Yin, Yaxi Li, Xin Liu, Xun Wang, Kaiqiang Song, Simin Ma, Shujian Liu, Sathish Reddy Indurthi, Haoyun Deng, Pengcheng He, Mingyuan Zhou, Song Wang |
| 2025 | ACL | KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding. | Zhangchen Xu, Yang Liu, Yueqin Yin, Mingyuan Zhou, Radha Poovendran |
| 2025 | CVPR | FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors. | Changlong Shi, He Zhao, Bingjie Zhang, Mingyuan Zhou, Dandan Guo, Yi Chang |
| 2025 | ICLR | Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models. | Tianqi Chen, Shujian Zhang, Mingyuan Zhou |
| 2025 | ICLR | Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer. | Xinyue Hu, Zhibin Duan, Bo Chen, Mingyuan Zhou |
| 2025 | ICLR | Advancing Graph Generation through Beta Diffusion. | Xinyang Liu, Yilin He, Bo Chen, Mingyuan Zhou |
| 2025 | ICLR | DRL: Decomposed Representation Learning for Tabular Anomaly Detection. | Hangting Ye, He Zhao, Wei Fan, Mingyuan Zhou, Dandan Guo, Yi Chang |
| 2025 | ICLR | Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation. | Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, Hai Huang |
| 2025 | ICLR | Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step. | Mingyuan Zhou, Huangjie Zheng, Yi Gu, Zhendong Wang, Hai Huang |
| 2025 | ICML | 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 |
| 2025 | ICML | 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 |
| 2024 | CVPR | 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 |
| 2024 | CVPR | 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 |
| 2024 | CVPR | 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 |
| 2024 | CVPR | UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures. | Mingyuan Zhou, Rakib Hyder, Ziwei Xuan, Guojun Qi |
| 2024 | ICLR | Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting. | Yuxin Li, Wenchao Chen, Xinyue Hu, Bo Chen, Baolin Sun, Mingyuan Zhou |
| 2024 | ICLR | Long-tailed Diffusion Models with Oriented Calibration. | Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang |
| 2024 | ICLR | 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 |
| 2024 | ICML | 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 |
| 2024 | ICML | A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. | Shentao Yang, Tianqi Chen, Mingyuan Zhou |
| 2024 | ICML | Switchable Decision: Dynamic Neural Generation Networks. | Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou |
| 2024 | ICML | Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. | Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang |
| 2024 | UAI | 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 |
| 2023 | AISTATS | Probabilistic Conformal Prediction Using Conditional Random Samples. | Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei |
| 2023 | AISTATS | Uncertainty-aware Unsupervised Video Hashing. | Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian |
| 2023 | CVPR | Class-Balancing Diffusion Models. | Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou, Ya Zhang |
| 2023 | CVPR | DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration. | Zhixin Wang, Ziying Zhang, Xiaoyun Zhang, Huangjie Zheng, Mingyuan Zhou, Ya Zhang, Yanfeng Wang |
| 2023 | ICCV | 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 |
| 2023 | ICLR | 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 |
| 2023 | ICLR | Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning. | Zhendong Wang, Jonathan J. Hunt, Mingyuan Zhou |
| 2023 | ICLR | Diffusion-GAN: Training GANs with Diffusion. | Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou |
| 2023 | ICLR | Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders. | Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou |
| 2023 | ICML | Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. | Tianqi Chen, Mingyuan Zhou |
| 2023 | ICML | Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process. | Zhibin Duan, Xinyang Liu, Yudi Su, Yishi Xu, Bo Chen, Mingyuan Zhou |
| 2023 | ICML | Prototype-oriented unsupervised anomaly detection for multivariate time series. | Yuxin Li, Wenchao Chen, Bo Chen, Dongsheng Wang, Long Tian, Mingyuan Zhou |
| 2023 | ICML | POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models. | Korawat Tanwisuth, Shujian Zhang, Huangjie Zheng, Pengcheng He, Mingyuan Zhou |
| 2022 | ICLR | Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. | Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou |
| 2022 | ICLR | 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 |
| 2022 | ICLR | Learning Prototype-oriented Set Representations for Meta-Learning. | Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha |
| 2022 | ICML | Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection. | Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou |
| 2022 | ICML | Bayesian Deep Embedding Topic Meta-Learner. | Zhibin Duan, Yishi Xu, Jianqiao Sun, Bo Chen, Wenchao Chen, Chaojie Wang, Mingyuan Zhou |
| 2022 | ICML | Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning. | Shentao Yang, Yihao Feng, Shujian Zhang, Mingyuan Zhou |
| 2022 | NAACL | ALLSH: Active Learning Guided by Local Sensitivity and Hardness. | Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou |
| 2022 | SENSYS | Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. | Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian |
| 2021 | ACL | EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering. | Zhibin Duan, Hao Zhang, Chaojie Wang, Zhengjue Wang, Bo Chen, Mingyuan Zhou |
| 2021 | AISTATS | Graph Gamma Process Linear Dynamical Systems. | Rahi Kalantari, Mingyuan Zhou |
| 2021 | AISTATS | Hyperbolic graph embedding with enhanced semi-implicit variational inference. | Ali Lotfi-Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan I. Tamir |
| 2021 | CVPR | Partition-Guided GANs. | Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li, Mingyuan Zhou |
| 2021 | CVPR | Adversarially Adaptive Normalization for Single Domain Generalization. | Xinjie Fan, Qifei Wang, Junjie Ke, Feng Yang, Boqing Gong, Mingyuan Zhou |
| 2021 | ICCV | Polarimetric Helmholtz Stereopsis. | Yuqi Ding, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jinwei Ye |
| 2021 | ICLR | Contextual Dropout: An Efficient Sample-Dependent Dropout Module. | Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou |
| 2021 | ICML | ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables. | Aleksandar Dimitriev, Mingyuan Zhou |
| 2021 | ICML | Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network. | Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou |
| 2021 | ICML | Bayesian Attention Belief Networks. | Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou |
| 2020 | AISTATS | Learnable Bernoulli Dropout for Bayesian Deep Learning. | Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian |
| 2020 | AISTATS | Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification. | Zhengjue Wang, Chaojie Wang, Hao Zhang, Zhibin Duan, Mingyuan Zhou, Bo Chen |
| 2020 | AISTATS | Discrete Action On-Policy Learning with Action-Value Critic. | Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou |
| 2020 | AISTATS | Variational Autoencoders for Sparse and Overdispersed Discrete Data. | He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou |
| 2020 | EMNLP | Friendly Topic Assistant for Transformer Based Abstractive Summarization. | Zhengjue Wang, Zhibin Duan, Hao Zhang, Chaojie Wang, Long Tian, Bo Chen, Mingyuan Zhou |
| 2020 | ICASSP | Arsm Gradient Estimator for Supervised Learning to Rank. | Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian |
| 2020 | ICASSP | Semi-Implicit Stochastic Recurrent Neural Networks. | Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian |
| 2020 | ICCP | 3D Face Reconstruction using Color Photometric Stereo with Uncalibrated Near Point Lights. | Zhang Chen, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jingyi Yu |
| 2020 | ICLR | Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling. | Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou |
| 2020 | ICLR | Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation. | Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou |
| 2020 | ICLR | Mutual Information Gradient Estimation for Representation Learning. | Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu |
| 2020 | ICLR | Meta-Learning without Memorization. | Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn |
| 2020 | ICML | Recurrent Hierarchical Topic-Guided RNN for Language Generation. | Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou |
| 2020 | ICML | Bayesian Graph Neural Networks with Adaptive Connection Sampling. | Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian |
| 2020 | ICML | Thompson Sampling via Local Uncertainty. | Zhendong Wang, Mingyuan Zhou |
| 2020 | IJCAI | Switching Poisson Gamma Dynamical Systems. | Wenchao Chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou |
| 2020 | UAI | Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. | Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian |
| 2019 | AISTATS | Deep Topic Models for Multi-label Learning. | Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai |
| 2019 | ICLR | ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks. | Mingzhang Yin, Mingyuan Zhou |
| 2019 | ICML | Locally Private Bayesian Inference for Count Models. | Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach |
| 2019 | ICML | Convolutional Poisson Gamma Belief Network. | Chaojie Wang, Bo Chen, Sucheng Xiao, Mingyuan Zhou |
| 2019 | ICML | ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. | Mingzhang Yin, Yuguang Yue, Mingyuan Zhou |
| 2018 | AAAI | Multimodal Poisson Gamma Belief Network. | Chaojie Wang, Bo Chen, Mingyuan Zhou |
| 2018 | AISTATS | Nonparametric Bayesian sparse graph linear dynamical systems. | Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou |
| 2018 | ICLR | WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling. | Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou |
| 2018 | ICML | Semi-Implicit Variational Inference. | Mingzhang Yin, Mingyuan Zhou |
| 2018 | ICML | Inter and Intra Topic Structure Learning with Word Embeddings. | He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou |
| 2018 | KDD | A Dual Markov Chain Topic Model for Dynamic Environments. | Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou |
| 2017 | ICML | Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC. | Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou |
| 2016 | CVPR | Rotational Crossed-Slit Light Fields. | Nianyi Li, Haiting Lin, Bilin Sun, Mingyuan Zhou, Jingyi Yu |
| 2016 | ICML | Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. | Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach |
| 2015 | AISTATS | Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices. | Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou |
| 2015 | AISTATS | Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction. | Mingyuan Zhou |
| 2012 | GECCO | A GPU-based implementation of an enhanced GEP algorithm. | Shuai Shao, Xiyang Liu, Mingyuan Zhou, Jiguo Zhan, Xin Liu, Yanli Chu, Hao Chen |
| 2012 | ICASSP | Online Bayesian dictionary learning for large datasets. | Lingbo Li, Jorge G. Silva, Mingyuan Zhou, Lawrence Carin |
| 2012 | ICML | Lognormal and Gamma Mixed Negative Binomial Regression. | Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin |
| 2012 | KDD | The contextual focused topic model. | Xu Chen, Mingyuan Zhou, Lawrence Carin |
| 2012 | UAI | Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. | Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin |
| 2011 | ICASSP | Joint dictionary learning and topic modeling for image clustering. | Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Carin |
| 2011 | ICASSP | Covariate-dependent dictionary learning and sparse coding. | Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin |
| 2011 | ICML | On the Integration of Topic Modeling and Dictionary Learning. | Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin |
| 2010 | ICIP | Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. | John W. Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin |