default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMingyuan Zhou
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Journal Articles
- 2024
[j28]Yuqi Ding
, Yu Ji, Zhang Chen, Mingyuan Zhou, Sing Bing Kang, Jinwei Ye:
Polarimetric Helmholtz Stereopsis. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4597-4611 (2024)- [j27]Ruiying Lu, Bo Chen, Dandan Guo, Dongsheng Wang, Mingyuan Zhou:
Hierarchical Topic-Aware Contextualized Transformers. IEEE ACM Trans. Audio Speech Lang. Process. 32: 841-852 (2024) - [j26]Chengzhi Wu, Julius Pfrommer, Mingyuan Zhou, Jürgen Beyerer:
Self-Supervised Generative-Contrastive Learning of Multi-Modal Euclidean Input for 3D Shape Latent Representations: A Dynamic Switching Approach. IEEE Trans. Multim. 26: 8432-8441 (2024) - 2023
- [j25]Quan Zhang, Yanxun Xu, Mei-Cheng Wang, Mingyuan Zhou:
Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates. J. Mach. Learn. Res. 24: 295:1-295:43 (2023) - [j24]Chaojie Wang, Bo Chen, Zhibin Duan, Wenchao Chen, Hao Zhang, Mingyuan Zhou:
Generative Text Convolutional Neural Network for Hierarchical Document Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4586-4604 (2023) - [j23]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Attraction and Contrastive Repulsion for Representation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j22]Hao Zhang, Chaojie Wang, Zhengjue Wang, Zhibin Duan, Bo Chen, Mingyuan Zhou, Ricardo Henao, Lawrence Carin:
Learning Hierarchical Document Graphs From Multilevel Sentence Relations. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4273-4285 (2023) - 2022
- [j21]Dandan Guo, Ruiying Lu, Bo Chen, Zequn Zeng, Mingyuan Zhou:
Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning. Int. J. Comput. Vis. 130(8): 1920-1937 (2022) - [j20]Chaojie Wang, Bo Chen, Sucheng Xiao, Zhengjue Wang, Hao Zhang, Penghui Wang, Ning Han, Mingyuan Zhou:
Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data. IEEE Trans. Cybern. 52(10): 11156-11171 (2022) - [j19]Wenchao Chen, Bo Chen, Yicheng Liu, Chaojie Wang, Xiaojun Peng, Hongwei Liu, Mingyuan Zhou:
Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning. IEEE Trans. Signal Process. 70: 2224-2238 (2022) - 2021
- [j18]Liangjian Wen, Haoli Bai, Lirong He, Yiji Zhou, Mingyuan Zhou, Zenglin Xu:
Gradient estimation of information measures in deep learning. Knowl. Based Syst. 224: 107046 (2021) - [j17]Wei Yang, Yingliang Zhang, Jinwei Ye, Yu Ji, Zhong Li, Mingyuan Zhou, Jingyi Yu:
Structure From Motion on XSlit Cameras. IEEE Trans. Pattern Anal. Mach. Intell. 43(5): 1691-1704 (2021) - [j16]Hao Zhang, Bo Chen, Yulai Cong, Dandan Guo, Hongwei Liu, Mingyuan Zhou:
Deep Autoencoding Topic Model With Scalable Hybrid Bayesian Inference. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4306-4322 (2021) - 2020
- [j15]Wenyuan Li, Zichen Wang, Yuguang Yue, Jiayun Li, William Speier, Mingyuan Zhou, Corey W. Arnold:
Semi-supervised learning using adversarial training with good and bad samples. Mach. Vis. Appl. 31(6): 49 (2020) - [j14]Mingyuan Zhou, Yuqi Ding, Yu Ji, S. Susan Young, Jingyi Yu, Jinwei Ye:
Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field. IEEE Trans. Pattern Anal. Mach. Intell. 42(7): 1594-1605 (2020) - [j13]Dandan Guo, Bo Chen, Wenchao Chen, Chaojie Wang, Hongwei Liu, Mingyuan Zhou:
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition. IEEE Trans. Signal Process. 68: 5795-5809 (2020) - 2019
- [j12]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Bayesian negative binomial regression for differential expression with confounding factors. Bioinform. 35(13): 2346 (2019) - [j11]Jinwei Ye, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jingyi Yu:
Content Aware Image Pre-Compensation. IEEE Trans. Pattern Anal. Mach. Intell. 41(7): 1545-1558 (2019) - 2018
- [j10]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Covariate-dependent negative binomial factor analysis of RNA sequencing data. Bioinform. 34(13): i61-i69 (2018) - [j9]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Bayesian negative binomial regression for differential expression with confounding factors. Bioinform. 34(19): 3349-3356 (2018) - 2017
- [j8]Quan Zhang, Mingyuan Zhou:
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression. J. Mach. Learn. Res. 18: 204:1-204:33 (2017) - 2016
- [j7]Mingyuan Zhou, Yulai Cong, Bo Chen:
Augmentable Gamma Belief Networks. J. Mach. Learn. Res. 17: 163:1-163:44 (2016) - 2015
- [j6]Mingyuan Zhou, Lawrence Carin:
Negative Binomial Process Count and Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 307-320 (2015) - [j5]Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies:
A Bayesian Nonparametric Approach to Image Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 346-358 (2015) - 2014
- [j4]David E. Carlson, Joshua T. Vogelstein, Qisong Wu, Wenzhao Lian, Mingyuan Zhou, Colin R. Stoetzner, Daryl Kipke, Douglas Weber, David B. Dunson, Lawrence Carin:
Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling. IEEE Trans. Biomed. Eng. 61(1): 41-54 (2014) - 2012
- [j3]Zhengming Xing, Mingyuan Zhou, Alexey Castrodad, Guillermo Sapiro, Lawrence Carin:
Dictionary Learning for Noisy and Incomplete Hyperspectral Images. SIAM J. Imaging Sci. 5(1): 33-56 (2012) - [j2]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Lingbo Li, Zhengming Xing, David B. Dunson, Guillermo Sapiro, Lawrence Carin:
Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. IEEE Trans. Image Process. 21(1): 130-144 (2012) - 2008
- [j1]Chengshi Zheng, Mingyuan Zhou, Xiaodong Li:
On the relationship of non-parametric methods for coherence function estimation. Signal Process. 88(11): 2863-2867 (2008)
Conference and Workshop Papers
- 2024
- [c129]Mingyuan Zhou, Rakib Hyder, Ziwei Xuan, Guojun Qi:
UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures. CVPR 2024: 1238-1248 - [c128]Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi, Yalin Wang:
OmniMotionGPT: Animal Motion Generation with Limited Data. CVPR 2024: 1249-1259 - [c127]Zilyu Ye, Jinxiu Liu, Jinjin Cao, Zhiyang Chen, Ziwei Xuan, Mingyuan Zhou, Qi Liu, Guo-Jun Qi:
OpenStory: A Large-Scale Open-Domain Dataset for Subject-Driven Visual Storytelling. CVPR Workshops 2024: 7953-7962 - [c126]Ruyi An, Yewen Li, Xu He, Pengjie Gu, Mengchen Zhao, Dong Li, Jianye Hao, Chaojie Wang, Bo An, Mingyuan Zhou:
Improving Unsupervised Hierarchical Representation With Reinforcement Learning. CVPR 2024: 22946-22956 - [c125]Yuxin Li, Wenchao Chen, Xinyue Hu, Bo Chen, Baolin Sun, Mingyuan Zhou:
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting. ICLR 2024 - [c124]Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang:
Long-tailed Diffusion Models with Oriented Calibration. ICLR 2024 - [c123]Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou:
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling. ICLR 2024 - [c122]Yuxin Li, Yaoxuan Feng, Bo Chen, Wenchao Chen, Yubiao Wang, Xinyue Hu, Baolin Sun, Chunhui Qu, Mingyuan Zhou:
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection. ICML 2024 - [c121]Shentao Yang, Tianqi Chen, Mingyuan Zhou:
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. ICML 2024 - [c120]Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou:
Switchable Decision: Dynamic Neural Generation Networks. ICML 2024 - [c119]Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang:
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. ICML 2024 - 2023
- [c118]Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian:
Uncertainty-aware Unsupervised Video Hashing. AISTATS 2023: 6722-6740 - [c117]Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei:
Probabilistic Conformal Prediction Using Conditional Random Samples. AISTATS 2023: 8814-8836 - [c116]Zhixin Wang, Ziying Zhang, Xiaoyun Zhang, Huangjie Zheng, Mingyuan Zhou, Ya Zhang, Yanfeng Wang:
DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration. CVPR 2023: 1704-1713 - [c115]Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou, Ya Zhang:
Class-Balancing Diffusion Models. CVPR 2023: 18434-18443 - [c114]Miaoge Li, Dongsheng Wang, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen, Mingyuan Zhou:
PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification. ICCV 2023: 15302-15312 - [c113]Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong, Mingyuan Zhou, Huan Wang:
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems. ICLR 2023 - [c112]Zhendong Wang, Jonathan J. Hunt, Mingyuan Zhou:
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning. ICLR 2023 - [c111]Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Diffusion-GAN: Training GANs with Diffusion. ICLR 2023 - [c110]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders. ICLR 2023 - [c109]Tianqi Chen, Mingyuan Zhou:
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. ICML 2023: 5367-5382 - [c108]Zhibin Duan, Xinyang Liu, Yudi Su, Yishi Xu, Bo Chen, Mingyuan Zhou:
Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process. ICML 2023: 8731-8746 - [c107]Yuxin Li, Wenchao Chen, Bo Chen, Dongsheng Wang, Long Tian, Mingyuan Zhou:
Prototype-oriented unsupervised anomaly detection for multivariate time series. ICML 2023: 19407-19424 - [c106]Korawat Tanwisuth, Shujian Zhang, Huangjie Zheng, Pengcheng He, Mingyuan Zhou:
POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models. ICML 2023: 33816-33832 - [c105]Zhibin Duan, Zhiyi Lv, Chaojie Wang, Bo Chen, Bo An, Mingyuan Zhou:
Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory. NeurIPS 2023 - [c104]Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang (Atlas) Wang, Mingyuan Zhou:
In-Context Learning Unlocked for Diffusion Models. NeurIPS 2023 - [c103]Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou:
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. NeurIPS 2023 - [c102]Yishi Xu, Jianqiao Sun, Yudi Su, Xinyang Liu, Zhibin Duan, Bo Chen, Mingyuan Zhou:
Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes. NeurIPS 2023 - [c101]Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou:
Preference-grounded Token-level Guidance for Language Model Fine-tuning. NeurIPS 2023 - [c100]Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng:
Beta Diffusion. NeurIPS 2023 - 2022
- [c99]Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou:
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. ICLR 2022 - [c98]Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama:
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. ICLR 2022 - [c97]Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha:
Learning Prototype-oriented Set Representations for Meta-Learning. ICLR 2022 - [c96]Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou:
Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection. ICML 2022: 3621-3633 - [c95]Zhibin Duan, Yishi Xu, Jianqiao Sun, Bo Chen, Wenchao Chen, Chaojie Wang, Mingyuan Zhou:
Bayesian Deep Embedding Topic Meta-Learner. ICML 2022: 5659-5670 - [c94]Shentao Yang, Yihao Feng, Shujian Zhang, Mingyuan Zhou:
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning. ICML 2022: 24980-25006 - [c93]Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
ALLSH: Active Learning Guided by Local Sensitivity and Hardness. NAACL-HLT (Findings) 2022: 1328-1342 - [c92]Dongsheng Wang, Yishi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou:
Knowledge-Aware Bayesian Deep Topic Model. NeurIPS 2022 - [c91]Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. NeurIPS 2022 - [c90]Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. NeurIPS 2022 - [c89]Xizewen Han, Huangjie Zheng, Mingyuan Zhou:
CARD: Classification and Regression Diffusion Models. NeurIPS 2022 - [c88]Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou:
A Variational Edge Partition Model for Supervised Graph Representation Learning. NeurIPS 2022 - [c87]Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Bo An, Mingyuan Zhou:
Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient. NeurIPS 2022 - [c86]Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou:
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding. NeurIPS 2022 - [c85]Shentao Yang, Shujian Zhang, Yihao Feng, Mingyuan Zhou:
A Unified Framework for Alternating Offline Model Training and Policy Learning. NeurIPS 2022 - [c84]Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian:
Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. SenSys 2022: 1109-1115 - 2021
- [c83]Zhibin Duan, Hao Zhang, Chaojie Wang, Zhengjue Wang, Bo Chen, Mingyuan Zhou:
EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering. ACL/IJCNLP (1) 2021: 2954-2967 - [c82]Ali Lotfi-Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan I. Tamir:
Hyperbolic graph embedding with enhanced semi-implicit variational inference. AISTATS 2021: 3439-3447 - [c81]Rahi Kalantari, Mingyuan Zhou:
Graph Gamma Process Linear Dynamical Systems. AISTATS 2021: 4060-4068 - [c80]Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li, Mingyuan Zhou:
Partition-Guided GANs. CVPR 2021: 5099-5109 - [c79]Xinjie Fan, Qifei Wang, Junjie Ke, Feng Yang, Boqing Gong, Mingyuan Zhou:
Adversarially Adaptive Normalization for Single Domain Generalization. CVPR 2021: 8208-8217 - [c78]Yuqi Ding, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jinwei Ye:
Polarimetric Helmholtz Stereopsis. ICCV 2021: 5017-5026 - [c77]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. ICLR 2021 - [c76]Aleksandar Dimitriev, Mingyuan Zhou:
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables. ICML 2021: 2717-2727 - [c75]Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou:
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network. ICML 2021: 2903-2913 - [c74]Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou:
Bayesian Attention Belief Networks. ICML 2021: 12413-12426 - [c73]Zhibin Duan, Yishi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou:
TopicNet: Semantic Graph-Guided Topic Discovery. NeurIPS 2021: 547-559 - [c72]Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou:
Convex Polytope Trees and its Application to VAE. NeurIPS 2021: 5038-5051 - [c71]Alek Dimitriev, Mingyuan Zhou:
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator. NeurIPS 2021: 13217-13229 - [c70]Shujian Zhang, Xinjie Fan, Huangjie Zheng, Korawat Tanwisuth, Mingyuan Zhou:
Alignment Attention by Matching Key and Query Distributions. NeurIPS 2021: 13444-13457 - [c69]Huangjie Zheng, Mingyuan Zhou:
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions. NeurIPS 2021: 14993-15006 - [c68]Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou:
A Prototype-Oriented Framework for Unsupervised Domain Adaptation. NeurIPS 2021: 17194-17208 - [c67]Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama:
Probabilistic Margins for Instance Reweighting in Adversarial Training. NeurIPS 2021: 23258-23269 - 2020
- [c66]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS 2020: 1684-1694 - [c65]Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou:
Discrete Action On-Policy Learning with Action-Value Critic. AISTATS 2020: 1977-1987 - [c64]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. AISTATS 2020: 3905-3916 - [c63]Zhengjue Wang, Chaojie Wang, Hao Zhang, Zhibin Duan, Mingyuan Zhou, Bo Chen:
Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification. AISTATS 2020: 3959-3969 - [c62]Zhengjue Wang, Zhibin Duan, Hao Zhang, Chaojie Wang, Long Tian, Bo Chen, Mingyuan Zhou:
Friendly Topic Assistant for Transformer Based Abstractive Summarization. EMNLP (1) 2020: 485-497 - [c61]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
Arsm Gradient Estimator for Supervised Learning to Rank. ICASSP 2020: 3157-3161 - [c60]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP 2020: 3342-3346 - [c59]Zhang Chen, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jingyi Yu:
3D Face Reconstruction using Color Photometric Stereo with Uncalibrated Near Point Lights. ICCP 2020: 1-12 - [c58]Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou:
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling. ICLR 2020 - [c57]Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou:
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation. ICLR 2020 - [c56]Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu:
Mutual Information Gradient Estimation for Representation Learning. ICLR 2020 - [c55]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. ICLR 2020 - [c54]Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou:
Recurrent Hierarchical Topic-Guided RNN for Language Generation. ICML 2020: 3810-3821 - [c53]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML 2020: 4094-4104 - [c52]Zhendong Wang, Mingyuan Zhou:
Thompson Sampling via Local Uncertainty. ICML 2020: 10115-10125 - [c51]Wenchao Chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou:
Switching Poisson Gamma Dynamical Systems. IJCAI 2020: 2029-2036 - [c50]Wenchao Chen, Chaojie Wang, Bo Chen, Yicheng Liu, Hao Zhang, Mingyuan Zhou:
Bidirectional Convolutional Poisson Gamma Dynamical Systems. NeurIPS 2020 - [c49]Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou:
Bayesian Attention Modules. NeurIPS 2020 - [c48]Chaojie Wang, Hao Zhang, Bo Chen, Dongsheng Wang, Zhengjue Wang, Mingyuan Zhou:
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network. NeurIPS 2020 - [c47]Yuguang Yue, Zhendong Wang, Mingyuan Zhou:
Implicit Distributional Reinforcement Learning. NeurIPS 2020 - [c46]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. UAI 2020: 540-549 - 2019
- [c45]Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai:
Deep Topic Models for Multi-label Learning. AISTATS 2019: 2849-2857 - [c44]Mingzhang Yin, Mingyuan Zhou:
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks. ICLR (Poster) 2019 - [c43]Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. ICML 2019: 5638-5648 - [c42]Chaojie Wang, Bo Chen, Sucheng Xiao, Mingyuan Zhou:
Convolutional Poisson Gamma Belief Network. ICML 2019: 6515-6525 - [c41]Mingzhang Yin, Yuguang Yue, Mingyuan Zhou:
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. ICML 2019: 7095-7104 - [c40]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. NeurIPS 2019: 781-792 - [c39]Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. NeurIPS 2019: 10700-10710 - [c38]Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS 2019: 10711-10722 - 2018
- [c37]Chaojie Wang, Bo Chen, Mingyuan Zhou:
Multimodal Poisson Gamma Belief Network. AAAI 2018: 2492-2499 - [c36]Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou:
Nonparametric Bayesian sparse graph linear dynamical systems. AISTATS 2018: 1952-1960 - [c35]Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou:
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling. ICLR (Poster) 2018 - [c34]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Variational Inference. ICML 2018: 5646-5655 - [c33]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Inter and Intra Topic Structure Learning with Word Embeddings. ICML 2018: 5887-5896 - [c32]Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou:
A Dual Markov Chain Topic Model for Dynamic Environments. KDD 2018: 1099-1108 - [c31]Mingyuan Zhou:
Parsimonious Bayesian deep networks. NeurIPS 2018: 3194-3204 - [c30]Quan Zhang, Mingyuan Zhou:
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks. NeurIPS 2018: 5007-5018 - [c29]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. NeurIPS 2018: 5841-5851 - [c28]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Dirichlet belief networks for topic structure learning. NeurIPS 2018: 7966-7977 - [c27]Dandan Guo, Bo Chen, Hao Zhang, Mingyuan Zhou:
Deep Poisson gamma dynamical systems. NeurIPS 2018: 8451-8461 - [c26]Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian:
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. NeurIPS 2018: 9133-9142 - 2017
- [c25]Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou:
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC. ICML 2017: 864-873 - 2016
- [c24]Nianyi Li, Haiting Lin, Bilin Sun, Mingyuan Zhou, Jingyi Yu:
Rotational Crossed-Slit Light Fields. CVPR 2016: 4405-4413 - [c23]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. ICML 2016: 2810-2819 - [c22]Aaron Schein, Hanna M. Wallach, Mingyuan Zhou:
Poisson-Gamma dynamical systems. NIPS 2016: 5006-5014 - 2015
- [c21]Mingyuan Zhou, Haiting Lin, Jingyi Yu, S. Susan Young:
Hybrid sensing face detection and recognition. AIPR 2015: 1-9 - [c20]Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou:
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices. AISTATS 2015 - [c19]Mingyuan Zhou:
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction. AISTATS 2015 - [c18]Mingyuan Zhou:
Nonparametric Bayesian matrix factorization for assortative networks. EUSIPCO 2015: 2776-2780 - [c17]Mingyuan Zhou, Yulai Cong, Bo Chen:
The Poisson Gamma Belief Network. NIPS 2015: 3043-3051 - [c16]Ayan Acharya, Dean Teffer, Jette Henderson, Marcus Tyler, Mingyuan Zhou, Joydeep Ghosh:
Gamma Process Poisson Factorization for Joint Modeling of Network and Documents. ECML/PKDD (1) 2015: 283-299 - 2014
- [c15]Mingyuan Zhou:
Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling. NIPS 2014: 3455-3463 - 2012
- [c14]Shuai Shao, Xiyang Liu, Mingyuan Zhou, Jiguo Zhan, Xin Liu, Yanli Chu, Hao Chen:
A GPU-based implementation of an enhanced GEP algorithm. GECCO 2012: 999-1006 - [c13]Lingbo Li, Jorge G. Silva, Mingyuan Zhou, Lawrence Carin:
Online Bayesian dictionary learning for large datasets. ICASSP 2012: 2157-2160 - [c12]Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin:
Lognormal and Gamma Mixed Negative Binomial Regression. ICML 2012 - [c11]Xu Chen, Mingyuan Zhou, Lawrence Carin:
The contextual focused topic model. KDD 2012: 96-104 - [c10]Mingyuan Zhou, Lawrence Carin:
Augment-and-Conquer Negative Binomial Processes. NIPS 2012: 2555-2563 - [c9]Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin:
Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. UAI 2012: 469-478 - [c8]Mingyuan Zhou, Lauren Hannah, David B. Dunson, Lawrence Carin:
Beta-Negative Binomial Process and Poisson Factor Analysis. AISTATS 2012: 1462-1471 - 2011
- [c7]Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Carin:
Joint dictionary learning and topic modeling for image clustering. ICASSP 2011: 2168-2171 - [c6]Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin:
Covariate-dependent dictionary learning and sparse coding. ICASSP 2011: 5824-5827 - [c5]Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin:
On the Integration of Topic Modeling and Dictionary Learning. ICML 2011: 625-632 - [c4]Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin:
Dependent Hierarchical Beta Process for Image Interpolation and Denoising. AISTATS 2011: 883-891 - 2010
- [c3]John W. Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin:
Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. ICIP 2010: 1869-1872 - [c2]Matthew L. Hill, Gang Hua, Apostol Natsev, John R. Smith, Lexing Xie, Bert Huang, Michele Merler, Hua Ouyang, Mingyuan Zhou:
IBM Research TRECVID-2010 Video Copy Detection and Multimedia Event Detection System. TRECVID 2010 - 2009
- [c1]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Guillermo Sapiro, Lawrence Carin:
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations. NIPS 2009: 2295-2303
Informal and Other Publications
- 2024
- [i119]Mingyuan Zhou, Rakib Hyder, Ziwei Xuan, Guojun Qi:
UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures. CoRR abs/2401.11078 (2024) - [i118]Shentao Yang, Tianqi Chen, Mingyuan Zhou:
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. CoRR abs/2402.08265 (2024) - [i117]Yueqin Yin, Zhendong Wang, Yi Gu, Hai Huang, Weizhu Chen, Mingyuan Zhou:
Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts. CoRR abs/2402.10958 (2024) - [i116]Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang:
Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization. CoRR abs/2402.14270 (2024) - [i115]Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang:
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. CoRR abs/2404.04057 (2024) - [i114]Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou:
Switchable Decision: Dynamic Neural Generation Networks. CoRR abs/2405.04513 (2024) - [i113]Tianyu Chen, Zhendong Wang, Mingyuan Zhou:
Diffusion Policies creating a Trust Region for Offline Reinforcement Learning. CoRR abs/2405.19690 (2024) - [i112]Yueqin Yin, Zhendong Wang, Yujia Xie, Weizhu Chen, Mingyuan Zhou:
Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment. CoRR abs/2405.20830 (2024) - [i111]Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, Hai Huang:
Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation. CoRR abs/2406.01561 (2024) - [i110]Xizewen Han, Mingyuan Zhou:
Diffusion Boosted Trees. CoRR abs/2406.01813 (2024) - [i109]Yi Gu, Zhendong Wang, Yueqin Yin, Yujia Xie, Mingyuan Zhou:
Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization. CoRR abs/2406.06382 (2024) - [i108]Yilin He, Xinyang Liu, Bo Chen, Mingyuan Zhou:
Advancing Graph Generation through Beta Diffusion. CoRR abs/2406.09357 (2024) - [i107]Zhibin Duan, Tiansheng Wen, Yifei Wang, Chen Zhu, Bo Chen, Mingyuan Zhou:
Contrastive Factor Analysis. CoRR abs/2407.21740 (2024) - [i106]Zhibin Duan, Tiansheng Wen, Muyao Wang, Bo Chen, Mingyuan Zhou:
A Non-negative VAE:the Generalized Gamma Belief Network. CoRR abs/2408.03388 (2024) - [i105]Zilyu Ye, Jinxiu Liu, Ruotian Peng, Jinjin Cao, Zhiyang Chen, Yiyang Zhang, Ziwei Xuan, Mingyuan Zhou, Xiaoqian Shen, Mohamed Elhoseiny, Qi Liu, Guo-Jun Qi:
Openstory++: A Large-scale Dataset and Benchmark for Instance-aware Open-domain Visual Storytelling. CoRR abs/2408.03695 (2024) - [i104]Xinyue Hu, Zhibin Duan, Xinyang Liu, Yuxin Li, Bo Chen, Mingyuan Zhou:
Disentangled Generative Graph Representation Learning. CoRR abs/2408.13471 (2024) - [i103]Tianqi Chen, Shujian Zhang, Mingyuan Zhou:
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models. CoRR abs/2409.11219 (2024) - [i102]Chaojie Wang, Xinyang Liu, Dongsheng Wang, Hao Zhang, Bo Chen, Mingyuan Zhou:
Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks. CoRR abs/2410.09696 (2024) - [i101]Mingyuan Zhou, Haoze Song, Wenjing Ye, Wei Wang, Zhilu Lai:
Parameter estimation of structural dynamics with neural operators enabled surrogate modeling. CoRR abs/2410.11712 (2024) - [i100]Mingyuan Zhou, Huangjie Zheng, Yi Gu, Zhendong Wang, Hai Huang:
Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step. CoRR abs/2410.14919 (2024) - [i99]Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj S. Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng:
One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation. CoRR abs/2410.21257 (2024) - 2023
- [i98]Chengzhi Wu, Julius Pfrommer, Mingyuan Zhou, Jürgen Beyerer:
Generative-Contrastive Learning for Self-Supervised Latent Representations of 3D Shapes from Multi-Modal Euclidean Input. CoRR abs/2301.04612 (2023) - [i97]Korawat Tanwisuth, Shujian Zhang, Pengcheng He, Mingyuan Zhou:
A Prototype-Oriented Clustering for Domain Shift with Source Privacy. CoRR abs/2302.03807 (2023) - [i96]Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong, Mingyuan Zhou, Huan Wang:
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems. CoRR abs/2302.10342 (2023) - [i95]Zhixin Wang, Xiaoyun Zhang, Ziying Zhang, Huangjie Zheng, Mingyuan Zhou, Ya Zhang, Yanfeng Wang:
DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration. CoRR abs/2303.06885 (2023) - [i94]Xinyang Liu, Dongsheng Wang, Miaoge Li, Zhibin Duan, Yishi Xu, Bo Chen, Mingyuan Zhou:
Patch-Token Aligned Bayesian Prompt Learning for Vision-Language Models. CoRR abs/2303.09100 (2023) - [i93]Mohammadreza Armandpour, Ali Sadeghian, Huangjie Zheng, Amir Sadeghian, Mingyuan Zhou:
Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond. CoRR abs/2304.04968 (2023) - [i92]Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou:
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. CoRR abs/2304.12526 (2023) - [i91]Korawat Tanwisuth, Shujian Zhang, Huangjie Zheng, Pengcheng He, Mingyuan Zhou:
POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models. CoRR abs/2305.00350 (2023) - [i90]Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou, Ya Zhang:
Class-Balancing Diffusion Models. CoRR abs/2305.00562 (2023) - [i89]Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou:
In-Context Learning Unlocked for Diffusion Models. CoRR abs/2305.01115 (2023) - [i88]Shujian Zhang, Chengyue Gong, Lemeng Wu, Xingchao Liu, Mingyuan Zhou:
AutoML-GPT: Automatic Machine Learning with GPT. CoRR abs/2305.02499 (2023) - [i87]Tianqi Chen, Mingyuan Zhou:
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. CoRR abs/2305.18375 (2023) - [i86]Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou:
Preference-grounded Token-level Guidance for Language Model Fine-tuning. CoRR abs/2306.00398 (2023) - [i85]Miaoge Li, Dongsheng Wang, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen, Mingyuan Zhou:
PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification. CoRR abs/2307.09066 (2023) - [i84]Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng:
Beta Diffusion. CoRR abs/2309.07867 (2023) - [i83]Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou:
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling. CoRR abs/2310.06389 (2023) - [i82]Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi, Yalin Wang:
OmniMotionGPT: Animal Motion Generation with Limited Data. CoRR abs/2311.18303 (2023) - [i81]Tianqi Chen, Yongfei Liu, Zhendong Wang, Jianbo Yuan, Quanzeng You, Hongxia Yang, Mingyuan Zhou:
Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts. CoRR abs/2312.01408 (2023) - 2022
- [i80]Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou:
A Variational Edge Partition Model for Supervised Graph Representation Learning. CoRR abs/2202.03233 (2022) - [i79]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs. CoRR abs/2202.06510 (2022) - [i78]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Truncated Diffusion Probabilistic Models. CoRR abs/2202.09671 (2022) - [i77]Shentao Yang, Zhendong Wang, Huangjie Zheng, Yihao Feng, Mingyuan Zhou:
A Regularized Implicit Policy for Offline Reinforcement Learning. CoRR abs/2202.09673 (2022) - [i76]Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou:
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. CoRR abs/2203.01570 (2022) - [i75]Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
ALLSH: Active Learning Guided by Local Sensitivity and Hardness. CoRR abs/2205.04980 (2022) - [i74]Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Diffusion-GAN: Training GANs with Diffusion. CoRR abs/2206.02262 (2022) - [i73]Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei:
Probabilistic Conformal Prediction Using Conditional Random Samples. CoRR abs/2206.06584 (2022) - [i72]Shentao Yang, Yihao Feng, Shujian Zhang, Mingyuan Zhou:
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning. CoRR abs/2206.07166 (2022) - [i71]Xizewen Han, Huangjie Zheng, Mingyuan Zhou:
CARD: Classification and Regression Diffusion Models. CoRR abs/2206.07275 (2022) - [i70]Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. CoRR abs/2208.02951 (2022) - [i69]Zhendong Wang, Jonathan J. Hunt, Mingyuan Zhou:
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning. CoRR abs/2208.06193 (2022) - [i68]Dongsheng Wang, Chaojie Wang, Bo Chen, Mingyuan Zhou:
Ordinal Graph Gamma Belief Network for Social Recommender Systems. CoRR abs/2209.05106 (2022) - [i67]Dongsheng Wang, Yishi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou:
Knowledge-Aware Bayesian Deep Topic Model. CoRR abs/2209.14228 (2022) - [i66]Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. CoRR abs/2210.04144 (2022) - [i65]Shentao Yang, Shujian Zhang, Yihao Feng, Mingyuan Zhou:
A Unified Framework for Alternating Offline Model Training and Policy Learning. CoRR abs/2210.05922 (2022) - [i64]Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou:
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding. CoRR abs/2210.10625 (2022) - 2021
- [i63]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. CoRR abs/2103.04181 (2021) - [i62]Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li, Mingyuan Zhou:
Partition-Guided GANs. CoRR abs/2104.00816 (2021) - [i61]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Conditional Transport for Representation Learning. CoRR abs/2105.03746 (2021) - [i60]Dandan Guo, Ruiying Lu, Bo Chen, Zequn Zeng, Mingyuan Zhou:
Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning. CoRR abs/2105.04143 (2021) - [i59]Alek Dimitriev, Mingyuan Zhou:
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables. CoRR abs/2105.14141 (2021) - [i58]Xinjie Fan, Qifei Wang, Junjie Ke, Feng Yang, Boqing Gong, Mingyuan Zhou:
Adversarially Adaptive Normalization for Single Domain Generalization. CoRR abs/2106.01899 (2021) - [i57]Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou:
Bayesian Attention Belief Networks. CoRR abs/2106.05251 (2021) - [i56]Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama:
Probabilistic Margins for Instance Reweighting in Adversarial Training. CoRR abs/2106.07904 (2021) - [i55]Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou:
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network. CoRR abs/2107.02757 (2021) - [i54]Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha:
Learning Prototype-oriented Set Representations for Meta-Learning. CoRR abs/2110.09140 (2021) - [i53]Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou:
A Prototype-Oriented Framework for Unsupervised Domain Adaptation. CoRR abs/2110.12024 (2021) - [i52]Shujian Zhang, Xinjie Fan, Huangjie Zheng, Korawat Tanwisuth, Mingyuan Zhou:
Alignment Attention by Matching Key and Query Distributions. CoRR abs/2110.12567 (2021) - [i51]Alek Dimitriev, Mingyuan Zhou:
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator. CoRR abs/2110.14002 (2021) - [i50]Zhibin Duan, Yishi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou:
TopicNet: Semantic Graph-Guided Topic Discovery. CoRR abs/2110.14286 (2021) - [i49]Arman Hasanzadeh, Mohammadreza Armandpour, Ehsan Hajiramezanali, Mingyuan Zhou, Nick Duffield, Krishna Narayanan:
Bayesian Graph Contrastive Learning. CoRR abs/2112.07823 (2021) - 2020
- [i48]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. CoRR abs/2002.05155 (2020) - [i47]Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu:
Mutual Information Gradient Estimation for Representation Learning. CoRR abs/2005.01123 (2020) - [i46]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. CoRR abs/2005.10477 (2020) - [i45]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR abs/2006.04064 (2020) - [i44]Hao Zhang, Bo Chen, Yulai Cong, Dandan Guo, Hongwei Liu, Mingyuan Zhou:
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference. CoRR abs/2006.08804 (2020) - [i43]Yuguang Yue, Zhendong Wang, Mingyuan Zhou:
Implicit Distributional Reinforcement Learning. CoRR abs/2007.06159 (2020) - [i42]Rahi Kalantari, Mingyuan Zhou:
Graph Gamma Process Generalized Linear Dynamical Systems. CoRR abs/2007.12852 (2020) - [i41]Dandan Guo, Bo Chen, Wenchao Chen, Chaojie Wang, Hongwei Liu, Mingyuan Zhou:
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition. CoRR abs/2009.13011 (2020) - [i40]Quan Zhang, Huangjie Zheng, Mingyuan Zhou:
MCMC-Interactive Variational Inference. CoRR abs/2010.02029 (2020) - [i39]Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou:
Bayesian Attention Modules. CoRR abs/2010.10604 (2020) - [i38]Mohammadreza Armandpour, Mingyuan Zhou:
Convex Polytope Trees. CoRR abs/2010.11266 (2020) - [i37]Ali Lotfi-Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan I. Tamir:
Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference. CoRR abs/2011.00194 (2020) - [i36]Chunyuan Li, Xiujun Li, Lei Zhang, Baolin Peng, Mingyuan Zhou, Jianfeng Gao:
Self-supervised Pre-training with Hard Examples Improves Visual Representations. CoRR abs/2012.13493 (2020) - [i35]Huangjie Zheng, Mingyuan Zhou:
ACT: Asymptotic Conditional Transport. CoRR abs/2012.14100 (2020) - 2019
- [i34]Yunhao Tang, Mingzhang Yin, Mingyuan Zhou:
Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy. CoRR abs/1903.05284 (2019) - [i33]Zhang Chen, Yu Ji, Mingyuan Zhou, Sing Bing Kang, Jingyi Yu:
3D Face Reconstruction Using Color Photometric Stereo with Uncalibrated Near Point Lights. CoRR abs/1904.02605 (2019) - [i32]Mingyuan Zhou, Yu Ji, Yuqi Ding, Jinwei Ye, S. Susan Young, Jingyi Yu:
Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field. CoRR abs/1904.04875 (2019) - [i31]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. CoRR abs/1905.00616 (2019) - [i30]Mingzhang Yin, Yuguang Yue, Mingyuan Zhou:
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. CoRR abs/1905.01413 (2019) - [i29]Chaojie Wang, Bo Chen, Sucheng Xiao, Mingyuan Zhou:
Convolutional Poisson Gamma Belief Network. CoRR abs/1905.05394 (2019) - [i28]Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou:
Variational Hetero-Encoder Randomized Generative Adversarial Networks for Joint Image-Text Modeling. CoRR abs/1905.08622 (2019) - [i27]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Generative Model. CoRR abs/1905.12659 (2019) - [i26]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. CoRR abs/1908.07078 (2019) - [i25]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. CoRR abs/1908.09710 (2019) - [i24]Wenyuan Li, Zichen Wang, Yuguang Yue, Jiayun Li, William Speier, Mingyuan Zhou, Corey W. Arnold:
Semi-supervised Learning using Adversarial Training with Good and Bad Samples. CoRR abs/1910.08540 (2019) - [i23]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. CoRR abs/1910.12819 (2019) - [i22]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. CoRR abs/1910.12991 (2019) - [i21]Zhendong Wang, Mingyuan Zhou:
Thompson Sampling via Local Uncertainty. CoRR abs/1910.13673 (2019) - [i20]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
ARSM Gradient Estimator for Supervised Learning to Rank. CoRR abs/1911.00465 (2019) - [i19]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. CoRR abs/1912.03820 (2019) - [i18]Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou:
Recurrent Hierarchical Topic-Guided Neural Language Models. CoRR abs/1912.10337 (2019) - [i17]Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou:
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation. CoRR abs/1912.13151 (2019) - 2018
- [i16]Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. CoRR abs/1803.08471 (2018) - [i15]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. CoRR abs/1805.08193 (2018) - [i14]Mingyuan Zhou:
Parsimonious Bayesian deep networks. CoRR abs/1805.08719 (2018) - [i13]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Variational Inference. CoRR abs/1805.11183 (2018) - [i12]Mingzhang Yin, Mingyuan Zhou:
ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models. CoRR abs/1807.11143 (2018) - [i11]Quan Zhang, Mingyuan Zhou:
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks. CoRR abs/1810.08564 (2018) - [i10]Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian:
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. CoRR abs/1810.09433 (2018) - [i9]Dandan Guo, Bo Chen, Hao Zhang, Mingyuan Zhou:
Deep Poisson gamma dynamical systems. CoRR abs/1810.11209 (2018) - [i8]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Dirichlet belief networks for topic structure learning. CoRR abs/1811.00717 (2018) - 2017
- [i7]Aaron Schein, Mingyuan Zhou, Hanna M. Wallach:
Poisson-Gamma Dynamical Systems. CoRR abs/1701.05573 (2017) - [i6]Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou:
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC. CoRR abs/1706.01724 (2017) - 2016
- [i5]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. CoRR abs/1606.01855 (2016) - 2015
- [i4]Mingyuan Zhou:
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction. CoRR abs/1501.06218 (2015) - 2012
- [i3]Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin:
Lognormal and Gamma Mixed Negative Binomial Regression. CoRR abs/1206.6456 (2012) - [i2]Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies:
A Bayesian Nonparametric Approach to Image Super-resolution. CoRR abs/1209.5019 (2012) - [i1]Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin:
Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. CoRR abs/1210.4872 (2012)
Coauthor Index
[j27] [j24] [j22] [j21] [j20] [j19] [j16] [j13] [j7] [c125] [c122] [c114] [c107] [c105] [c99] [c96] [c95] [c92] [c88] [c87] [c86] [c83] [c75] [c74] [c73] [c68] [c63] [c62] [c58] [c54] [c51] [c50] [c49] [c48] [c42] [c37] [c35] [c27] [c25] [c17] [i106] [i104] [i102] [i94] [i85] [i80] [i76] [i68] [i67] [i64] [i60] [i57] [i55] [i53] [i50] [i44] [i41] [i39] [i29] [i28] [i18] [i9] [i6]
Krishna Narayanan 0001
aka: Krishna R. Narayanan
aka: Krishna R. Narayanan
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-10 21:44 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
