| Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley The Journal of Machine Learning Research 14 (1), 1303-1347, 2013 | 1383 | 2013 |
| Online variational inference for the hierarchical Dirichlet process C Wang, J Paisley, D Blei Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 363 | 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 | 352* | 2012 |
| Variational Bayesian Inference with Stochastic Search J Paisley, DM Blei, MI Jordan Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012 | 279 | 2012 |
| Nonparametric factor analysis with beta process priors J Paisley, L Carin Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 275 | 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, 2295-2303, 2009 | 256* | 2009 |
| Removing rain from single images via a deep detail network X Fu, J Huang, D Zeng, Y Huang, X Ding, J Paisley Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 178 | 2017 |
| 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 | 171 | 2010 |
| 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 | 166 | 2017 |
| Nested hierarchical Dirichlet processes J Paisley, C Wang, DM Blei, MI Jordan IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2), 256-270, 2014 | 162 | 2014 |
| Topicrnn: A recurrent neural network with long-range semantic dependency AB Dieng, C Wang, J Gao, J Paisley arXiv preprint arXiv:1611.01702, 2016 | 104 | 2016 |
| 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 | 99 | 2016 |
| Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI Y Huang, J Paisley, Q Lin, X Ding, X Fu, XP Zhang Image Processing, IEEE Transactions on 23 (12), 5007-5019, 2014 | 96 | 2014 |
| Music analysis using hidden markov mixture models Y Qi, JW Paisley, L Carin Signal Processing, IEEE Transactions on 55 (11), 5209-5224, 2007 | 80 | 2007 |
| The discrete infinite logistic normal distribution J Paisley, C Wang, D Blei Bayesian Analysis 7 (2), 235-272, 2012 | 78* | 2012 |
| The discrete infinite logistic normal distribution for mixed-membership modeling J Paisley, C Wang, D Blei Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 71 | 2011 |
| A stick-breaking construction of the beta process JW Paisley, AK Zaas, CW Woods, GS Ginsburg, L Carin Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010 | 70 | 2010 |
| Hidden Markov models with stick-breaking priors J Paisley, L Carin IEEE Transactions on Signal Processing 57 (10), 3905-3917, 2009 | 64 | 2009 |
| Combinatorial clustering and the beta negative binomial process T Broderick, L Mackey, J Paisley, MI Jordan IEEE transactions on pattern analysis and machine intelligence 37 (2), 290-306, 2014 | 62 | 2014 |
| 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 | 56 | 2018 |
David BleiProfessor of Statistics and Computer Science, Columbia University確認したメール アドレス: columbia.edu
