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2020 – today
- 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)- [i69]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) - [i68]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs. CoRR abs/2202.06510 (2022) - [i67]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Truncated Diffusion Probabilistic Models. CoRR abs/2202.09671 (2022) - [i66]Shentao Yang, Zhendong Wang, Huangjie Zheng, Yihao Feng, Mingyuan Zhou:
A Regularized Implicit Policy for Offline Reinforcement Learning. CoRR abs/2202.09673 (2022) - [i65]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) - [i64]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) - 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