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Erik B. Sudderth
Erik B. Sudderth
Professor of Computer Science, UC Irvine
Verified email at uci.edu - Homepage
Title
Cited by
Cited by
Year
Nonparametric belief propagation
EB Sudderth, AT Ihler, WT Freeman, AS Willsky
IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003
580*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
515*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
4232005
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
3342008
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
3152004
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
2462004
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
2452011
Nonparametric Bayesian learning of switching linear dynamical systems
E Fox, E Sudderth, M Jordan, A Willsky
Advances in neural information processing systems 21, 2008
2432008
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
2382008
Graphical models for visual object recognition and tracking
EB Sudderth
Massachusetts Institute of Technology, 2006
2382006
Shared segmentation of natural scenes using dependent Pitman-Yor processes
E Sudderth, M Jordan
Advances in neural information processing systems 21, 2008
2172008
Describing visual scenes using transformed dirichlet processes
A Torralba, A Willsky, E Sudderth, W Freeman
Advances in neural information processing systems 18, 2005
1842005
Sharing features among dynamical systems with beta processes
E Fox, M Jordan, E Sudderth, A Willsky
Advances in neural information processing systems 22, 2009
1732009
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
1482010
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
1482010
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
1422012
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
1352016
Memoized online variational inference for Dirichlet process mixture models
MC Hughes, E Sudderth
Advances in neural information processing systems 26, 2013
1112013
Efficient multiscale sampling from products of Gaussian mixtures
A Ihler, E Sudderth, W Freeman, A Willsky
Advances in Neural Information Processing Systems 16, 2003
1092003
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
1072014
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