John Paisley

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Coauteurs

Xinghao DingAdresse e-mail validée de xmu.edu.cn
David BleiProfessor of Statistics and Computer Science, Columbia UniversityAdresse e-mail validée de columbia.edu
Lawrence CarinProfessor of Electrical and Computer Engineering, Duke UniversityAdresse e-mail validée de ece.duke.edu
Yue HuangAssociate Professor, Xiamen UniversityAdresse e-mail validée de xmu.edu.cn
Chong WangHead of AML Research at ByteDanceAdresse e-mail validée de cs.princeton.edu
Xueyang Fu (傅雪阳)University of Science and Technology of ChinaAdresse e-mail validée de ustc.edu.cn
Mingyuan ZhouAssociate Professor, University of Texas at AustinAdresse e-mail validée de mccombs.utexas.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
David DunsonArts & Sciences Professor of Statistical Science & MathematicsAdresse e-mail validée de duke.edu
Lu RenYahoo! IncAdresse e-mail validée de yahoo-inc.com
Delu ZengProfessor with South China University of TechnologyAdresse e-mail validée de scut.edu.cn
Jiabin HuangUnder postgraduate student of electronic and communication engineering, Xiamen UniversityAdresse e-mail validée de stu.xmu.edu.cn
Guillermo SapiroJames B. Duke Professor at Duke University and Senior Research Scientist at Apple, Inc.Adresse e-mail validée de duke.edu
Liyan SunXiamen UniversityAdresse e-mail validée de stu.xmu.edu.cn
Aonan ZhangByteDanceAdresse e-mail validée de bytedance.com
Minhua ChenInteractions LLCAdresse e-mail validée de interactions.com
San GultekinVerizon MediaAdresse e-mail validée de columbia.edu
Adji Bousso DiengColumbia UniversityAdresse e-mail validée de columbia.edu
Matthew D. HoffmanResearch Scientist, Google ResearchAdresse e-mail validée de google.com
Zhiwen FanXiamen UniversityAdresse e-mail validée de stu.xmu.edu.cn

John Paisley

Columbia University

Adresse e-mail validée de columbia.edu - Page d'accueil

Bayesian statistics machine learning signal processing


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley Journal of Machine Learning Research 14 (1), 1303-1347, 2013	1879	2013
Online variational inference for the hierarchical Dirichlet process C Wang, J Paisley, D Blei Artificial Intelligence and Statistics (AISTATS), 2011	427	2011
Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images M Zhou, H Chen, J Paisley, L Ren, L Li, Z Xing, D Dunson, G Sapiro, ... IEEE Transactions on Image Processing 21 (1), 130-144, 2012	398	2012
Variational Bayesian Inference with Stochastic Search J Paisley, DM Blei, MI Jordan International Conference on Machine Learning (ICML), 2012	376	2012
Removing rain from single images via a deep detail network X Fu, J Huang, D Zeng, Y Huang, X Ding, J Paisley IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017	366	2017
Clearing the skies: A deep network architecture for single-image rain removal X Fu, J Huang, X Ding, Y Liao, J Paisley IEEE Transactions on Image Processing 26 (6), 2944-2956, 2017	341	2017
Nonparametric factor analysis with beta process priors J Paisley, L Carin International Conference on Machine Learning (ICML), 2009	301	2009
Non-parametric Bayesian dictionary learning for sparse image representations M Zhou, H Chen, J Paisley, L Ren, G Sapiro, L Carin Advances in Neural Information Processing Systems, 2009	293	2009
Nested hierarchical Dirichlet processes J Paisley, C Wang, DM Blei, MI Jordan IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2), 256-270, 2015	198	2015
Compressive sensing on manifolds using a nonparametric mixture of factor analyzers: Algorithm and performance bounds M Chen, J Silva, J Paisley, C Wang, D Dunson, L Carin IEEE Transactions on Signal Processing 58 (12), 6140-6155, 2010	192	2010
A fusion-based enhancing method for weakly illuminated images X Fu, D Zeng, Y Huang, Y Liao, X Ding, J Paisley Signal Processing 129, 82-96, 2016	178	2016
Topicrnn: A recurrent neural network with long-range semantic dependency AB Dieng, C Wang, J Gao, J Paisley International Conference on Learning Representations (ICLR), 2017	157	2017
PanNet: A deep network architecture for pan-sharpening J Yang, X Fu, Y Hu, Y Huang, X Ding, J Paisley IEEE International Conference on Computer Vision (ICCV), 2017	132	2017
Hyperspectral image classification with Markov random fields and a convolutional neural network X Cao, F Zhou, L Xu, D Meng, Z Xu, J Paisley IEEE Transactions on Image Processing 27 (5), 2354-2367, 2018	123	2018
Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI Y Huang, J Paisley, Q Lin, X Ding, X Fu, XP Zhang IEEE Transactions on Image Processing 23 (12), 5007-5019, 2014	119	2014
Fully supervised speaker diarization A Zhang, Q Wang, Z Zhu, J Paisley, C Wang IEEE International Conference on Acoustics, Speech and Signal Processing, 2019	100	2019
Music analysis using hidden markov mixture models Y Qi, JW Paisley, L Carin IEEE Transactions on Signal Processing 55 (11), 5209-5224, 2007	91	2007
Variational Inference via Upper Bound Minimization AB Dieng, D Tran, R Ranganath, J Paisley, D Blei Advances in Neural Information Processing Systems, 2017	87	2017
The discrete infinite logistic normal distribution J Paisley, C Wang, D Blei Bayesian Analysis 7 (2), 235-272, 2012	86*	2012
A stick-breaking construction of the beta process J Paisley, AK Zaas, CW Woods, GS Ginsburg, L Carin International Conference on Machine Learning (ICML), 2010	82	2010

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