John Paisley

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Xinghao DingDirección de correo verificada de xmu.edu.cn
Yue HuangProfessor, Xiamen UniversityDirección de correo verificada de xmu.edu.cn
David BleiProfessor of Statistics and Computer Science, Columbia UniversityDirección de correo verificada de columbia.edu
Lawrence CarinDuke UniversityDirección de correo verificada de duke.edu
Xueyang Fu (傅雪阳)University of Science and Technology of ChinaDirección de correo verificada de ustc.edu.cn
Chong WangAppleDirección de correo verificada de cs.princeton.edu
Delu ZengProfessor with EE in South China University of TechnologyDirección de correo verificada de scut.edu.cn
Mingyuan ZhouAssociate Professor, University of Texas at AustinDirección de correo verificada de mccombs.utexas.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Liyan SunStanford UniversityDirección de correo verificada de stanford.edu
Jiabin HuangUnder postgraduate student of electronic and communication engineering, Xiamen UniversityDirección de correo verificada de stu.xmu.edu.cn
David DunsonArts & Sciences Professor of Statistical Science & MathematicsDirección de correo verificada de duke.edu
Lu RenYahoo! IncDirección de correo verificada de yahoo-inc.com
Aonan ZhangAppleDirección de correo verificada de apple.com
San GultekinYahoo! Research, Columbia UniversityDirección de correo verificada de columbia.edu
Zhiwen FanUniversity of Texas at AustinDirección de correo verificada de utexas.edu
Guillermo SapiroJames B. Duke Professor, Duke University; Distinguished Engineer, Health AI Lead, Apple, Inc.Dirección de correo verificada de duke.edu
Matthew D. HoffmanResearch Scientist, Google ResearchDirección de correo verificada de google.com
Adji Bousso DiengAssistant Professor of Computer Science, Princeton UniversityDirección de correo verificada de princeton.edu
Minhua ChenMetaDirección de correo verificada de alumni.duke.edu

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John Paisley

Columbia University

Dirección de correo verificada de columbia.edu - Página principal


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley Journal of Machine Learning Research 14 (1), 1303-1347, 2013	2863	2013
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	976	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	799	2017
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	602	2016
Variational Bayesian Inference with Stochastic Search J Paisley, DM Blei, MI Jordan International Conference on Machine Learning (ICML), 2012	571	2012
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	541	2017
Online variational inference for the hierarchical Dirichlet process C Wang, J Paisley, D Blei Artificial Intelligence and Statistics (AISTATS), 2011	539	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	460	2012
Nonparametric factor analysis with beta process priors J Paisley, L Carin International Conference on Machine Learning (ICML), 2009	346	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	323	2009
Lightweight pyramid networks for image deraining X Fu, B Liang, Y Huang, X Ding, J Paisley IEEE Transactions on Neural Networks and Learning Systems, 2019	321	2019
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	309	2018
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	289	2015
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	264	2017
Fully supervised speaker diarization A Zhang, Q Wang, Z Zhu, J Paisley, C Wang IEEE International Conference on Acoustics, Speech and Signal Processing, 2019	239	2019
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	202	2010
Variational Inference via Upper Bound Minimization AB Dieng, D Tran, R Ranganath, J Paisley, D Blei Advances in Neural Information Processing Systems, 2017	174	2017
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	155	2014
Global explanations of neural networks: Mapping the landscape of predictions M Ibrahim, M Louie, C Modarres, J Paisley Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 279-287, 2019	122*	2019
Bayesian poisson tensor factorization for inferring multilateral relations from sparse dyadic event counts A Schein, J Paisley, DM Blei, H Wallach ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015	121*	2015

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