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2020 – today
- 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) - [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 - [i115]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) - [i114]Shentao Yang, Tianqi Chen, Mingyuan Zhou:
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. CoRR abs/2402.08265 (2024) - [i113]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) - [i112]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) - [i111]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) - [i110]Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou:
Switchable Decision: Dynamic Neural Generation Networks. CoRR abs/2405.04513 (2024) - [i109]Tianyu Chen, Zhendong Wang, Mingyuan Zhou:
Diffusion Policies creating a Trust Region for Offline Reinforcement Learning. CoRR abs/2405.19690 (2024) - [i108]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) - [i107]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) - [i106]Xizewen Han, Mingyuan Zhou:
Diffusion Boosted Trees. CoRR abs/2406.01813 (2024) - [i105]Yi Gu, Zhendong Wang, Yueqin Yin, Yujia Xie, Mingyuan Zhou:
Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization. CoRR abs/2406.06382 (2024) - [i104]Yilin He, Xinyang Liu, Bo Chen, Mingyuan Zhou:
Advancing Graph Generation through Beta Diffusion. CoRR abs/2406.09357 (2024) - [i103]Zhibin Duan, Tiansheng Wen, Yifei Wang, Chen Zhu, Bo Chen, Mingyuan Zhou:
Contrastive Factor Analysis. CoRR abs/2407.21740 (2024) - [i102]Zhibin Duan, Tiansheng Wen, Muyao Wang, Bo Chen, Mingyuan Zhou:
A Non-negative VAE:the Generalized Gamma Belief Network. CoRR abs/2408.03388 (2024) - [i101]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) - [i100]Xinyue Hu, Zhibin Duan, Xinyang Liu, Yuxin Li, Bo Chen, Mingyuan Zhou:
Disentangled Generative Graph Representation Learning. CoRR abs/2408.13471 (2024) - [i99]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) - 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) - [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 - [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
- [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) - [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 - [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
- [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) - [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 - [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
- [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) - [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 - [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)
2010 – 2019
- 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) - [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 - [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
- [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) - [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 - [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
- [j8]Quan Zhang, Mingyuan Zhou:
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression. J. Mach. Learn. Res. 18: 204:1-204:33 (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 - [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
- [j7]Mingyuan Zhou, Yulai Cong, Bo Chen:
Augmentable Gamma Belief Networks. J. Mach. Learn. Res. 17: 163:1-163:44 (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 - [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
- [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) - [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 - [i4]Mingyuan Zhou:
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction. CoRR abs/1501.06218 (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) - [c15]Mingyuan Zhou:
Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling. NIPS 2014: 3455-3463 - 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) - [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 - [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) - 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
2000 – 2009
- 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 - 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)
Coauthor Index
[j27] [c125] [c122] [i102] [i100] [j24] [j22] [c114] [c107] [c105] [i94] [i85] [j21] [j20] [j19] [c99] [c96] [c95] [c92] [c88] [c87] [c86] [i80] [i76] [i68] [i67] [i64] [j16] [c83] [c75] [c74] [c73] [c68] [i60] [i57] [i55] [i53] [i50] [j13] [c63] [c62] [c58] [c54] [c51] [c50] [c49] [c48] [i44] [i41] [i39] [c42] [i29] [i28] [i18] [c37] [c35] [c27] [i9] [c25] [i6] [j7] [c17]
Krishna Narayanan 0001
aka: Krishna R. Narayanan
aka: Krishna R. Narayanan
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