| Nonparametric belief propagation EB Sudderth, AT Ihler, WT Freeman, AS Willsky IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003 | 583* | 2003 |
| A sticky HDP-HMM with application to speaker diarization EB Fox, EB Sudderth, MI Jordan, AS Willsky The Annals of Applied Statistics, 1020-1056, 2011 | 510* | 2011 |
| Learning hierarchical models of scenes, objects, and parts EB Sudderth, A Torralba, WT Freeman, AS Willsky Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 2 …, 2005 | 421 | 2005 |
| An HDP-HMM for systems with state persistence EB Fox, EB Sudderth, MI Jordan, AS Willsky Proceedings of the 25th international conference on Machine learning, 312-319, 2008 | 334 | 2008 |
| Distributed occlusion reasoning for tracking with nonparametric belief propagation E Sudderth, M Mandel, W Freeman, A Willsky Advances in neural information processing systems 17, 2004 | 314 | 2004 |
| Visual hand tracking using nonparametric belief propagation EB Sudderth, MI Mandel, WT Freeman, AS Willsky 2004 Conference on Computer Vision and Pattern Recognition Workshop, 189-189, 2004 | 248 | 2004 |
| Bayesian nonparametric inference of switching dynamic linear models E Fox, EB Sudderth, MI Jordan, AS Willsky IEEE Transactions on Signal Processing 59 (4), 1569-1585, 2011 | 244 | 2011 |
| Nonparametric Bayesian learning of switching linear dynamical systems E Fox, E Sudderth, M Jordan, A Willsky Advances in neural information processing systems 21, 2008 | 241 | 2008 |
| Describing visual scenes using transformed objects and parts EB Sudderth, A Torralba, WT Freeman, AS Willsky International Journal of Computer Vision 77 (1), 291-330, 2008 | 237 | 2008 |
| Graphical models for visual object recognition and tracking EB Sudderth Massachusetts Institute of Technology, 2006 | 237 | 2006 |
| Shared segmentation of natural scenes using dependent Pitman-Yor processes E Sudderth, M Jordan Advances in neural information processing systems 21, 2008 | 216 | 2008 |
| Describing visual scenes using transformed dirichlet processes A Torralba, A Willsky, E Sudderth, W Freeman Advances in neural information processing systems 18, 2005 | 187 | 2005 |
| Sharing features among dynamical systems with beta processes E Fox, M Jordan, E Sudderth, A Willsky Advances in neural information processing systems 22, 2009 | 170 | 2009 |
| Layered image motion with explicit occlusions, temporal consistency, and depth ordering D Sun, E Sudderth, M Black Advances in Neural Information Processing Systems 23, 2010 | 146 | 2010 |
| Layered image motion with explicit occlusions, temporal consistency, and depth ordering D Sun, E Sudderth, M Black Advances in Neural Information Processing Systems 23, 2010 | 146 | 2010 |
| Layered segmentation and optical flow estimation over time D Sun, EB Sudderth, MJ Black 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1768-1775, 2012 | 139 | 2012 |
| Three-dimensional object detection and layout prediction using clouds of oriented gradients Z Ren, EB Sudderth Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 134 | 2016 |
| Efficient multiscale sampling from products of Gaussian mixtures A Ihler, E Sudderth, W Freeman, A Willsky Advances in Neural Information Processing Systems 16, 2003 | 110 | 2003 |
| Memoized online variational inference for Dirichlet process mixture models MC Hughes, E Sudderth Advances in neural information processing systems 26, 2013 | 108 | 2013 |
| Joint modeling of multiple time series via the beta process with application to motion capture segmentation EB Fox, MC Hughes, EB Sudderth, MI Jordan The Annals of Applied Statistics 8 (3), 1281-1313, 2014 | 103 | 2014 |
Alan S. WillskyProfessor of EECS, MIT在 mit.edu 的电子邮件经过验证
