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2020 – today
- 2023
[j22]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)- [i84]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) - [i83]Korawat Tanwisuth, Shujian Zhang, Pengcheng He, Mingyuan Zhou:
A Prototype-Oriented Clustering for Domain Shift with Source Privacy. CoRR abs/2302.03807 (2023) - [i82]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) - [i81]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) - 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) - [c91]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 - [c90]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 - [c89]Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha:
Learning Prototype-oriented Set Representations for Meta-Learning. ICLR 2022 - [c88]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 - [c87]Zhibin Duan, Yishi Xu, Jianqiao Sun, Bo Chen, Wenchao Chen, Chaojie Wang, Mingyuan Zhou:
Bayesian Deep Embedding Topic Meta-Learner. ICML 2022: 5659-5670 - [c86]Shentao Yang, Yihao Feng, Shujian Zhang, Mingyuan Zhou:
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning. ICML 2022: 24980-25006 - [c85]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 - [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<