| Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley Journal of Machine Learning Research 14 (1), 1303-1347, 2013 | 1459 | 2013 |
| Online variational inference for the hierarchical Dirichlet process C Wang, J Paisley, D Blei Artificial Intelligence and Statistics (AISTATS), 2011 | 367 | 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 | 365* | 2012 |
| Variational Bayesian Inference with Stochastic Search J Paisley, DM Blei, MI Jordan International Conference on Machine Learning (ICML), 2012 | 299 | 2012 |
| Nonparametric factor analysis with beta process priors J Paisley, L Carin International Conference on Machine Learning (ICML), 2009 | 283 | 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 | 263* | 2009 |
| 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 | 212 | 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 | 198 | 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 | 175 | 2010 |
| 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 | 167 | 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 | 105 | 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 | 103 | 2016 |
| 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 | 98 | 2014 |
| Music analysis using hidden markov mixture models Y Qi, JW Paisley, L Carin IEEE Transactions on Signal Processing 55 (11), 5209-5224, 2007 | 81 | 2007 |
| The discrete infinite logistic normal distribution J Paisley, C Wang, D Blei Bayesian Analysis 7 (2), 235-272, 2012 | 79* | 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 | 71 | 2010 |
| 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 | 65 | 2018 |
| Hidden Markov models with stick-breaking priors J Paisley, L Carin IEEE Transactions on Signal Processing 57 (10), 3905-3917, 2009 | 65 | 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, 2015 | 62 | 2015 |
| 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 | 55* | 2015 |
David BleiProfessor of Statistics and Computer Science, Columbia University確認したメール アドレス: columbia.edu
