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 and facial appearance estimation
EB Sudderth, AT Ihler, WT Freeman, AS Willsky
805*2002
Nonparametric belief propagation
EB Sudderth, AT Ihler, WT Freeman, AS Willsky
IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003
569*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
462*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
4082005
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
3142008
Nonparametric belief propagation
EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky
Communications of the ACM 53 (10), 95-103, 2010
2992010
Graphical models for visual object recognition and tracking
EB Sudderth
Massachusetts Institute of Technology, 2006
2262006
Describing visual scenes using transformed objects and parts
EB Sudderth, A Torralba, WT Freeman, AS Willsky
International Journal of Computer Vision 77 (1-3), 291-330, 2008
2252008
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
2252004
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
2082011
Nonparametric Bayesian learning of switching linear dynamical systems
E Fox, E Sudderth, M Jordan, A Willsky
Advances in neural information processing systems 21, 457-464, 2008
2072008
Shared segmentation of natural scenes using dependent Pitman-Yor processes
E Sudderth, M Jordan
Advances in neural information processing systems 21, 1585-1592, 2008
2022008
Describing visual scenes using transformed dirichlet processes
A Torralba, A Willsky, E Sudderth, W Freeman
Advances in neural information processing systems 18, 1297-1304, 2005
1852005
Sharing features among dynamical systems with beta processes
E Fox, M Jordan, E Sudderth, A Willsky
Advances in neural information processing systems 22, 549-557, 2009
1582009
Layered image motion with explicit occlusions, temporal consistency, and depth ordering
D Sun, E Sudderth, M Black
Advances in Neural Information Processing Systems 23, 2226-2234, 2010
1302010
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
1252012
Efficient multiscale sampling from products of Gaussian mixtures
AT Ihler, EB Sudderth, WT Freeman, AS Willsky
Advances in Neural Information Processing Systems, 1-8, 2004
1032004
Embedded trees: Estimation of Gaussian processes on graphs with cycles
EB Sudderth, MJ Wainwright, AS Willsky
IEEE Transactions on Signal Processing 52 (11), 3136-3150, 2004
992004
Learning multiscale representations of natural scenes using Dirichlet processes
JJ Kivinen, EB Sudderth, MI Jordan
2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007
982007
Truly nonparametric online variational inference for hierarchical Dirichlet processes
M Bryant, E Sudderth
Advances in Neural Information Processing Systems 25, 2699-2707, 2012
962012
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