Erik B. Sudderth
Erik B. Sudderth
Associate Professor of Computer Science, UC Irvine
確認したメール アドレス: uci.edu - ホームページ
タイトル引用先
Nonparametric belief propagation
EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky
Communications of the ACM 53 (10), 95-103, 2010
6892010
Nonparametric belief propagation
EB Sudderth, AT Ihler, WT Freeman, AS Willsky
IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003
689*2003
A sticky HDP-HMM with application to speaker diarization
EB Fox, EB Sudderth, MI Jordan, AS Willsky
The Annals of Applied Statistics 5 (2A), 1020-1056, 2011
387*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
3852005
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
2782008
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
2162008
Graphical models for visual object recognition and tracking
EB Sudderth
Massachusetts Institute of Technology, 2006
2132006
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
2072004
Shared segmentation of natural scenes using dependent Pitman-Yor processes
EB Sudderth, MI Jordan
Advances in neural information processing systems, 1585-1592, 2009
1842009
Describing visual scenes using transformed dirichlet processes
A Torralba, AS Willsky, EB Sudderth, WT Freeman
Advances in neural information processing systems, 1297-1304, 2006
1742006
Nonparametric Bayesian learning of switching linear dynamical systems
E Fox, EB Sudderth, MI Jordan, AS Willsky
Advances in Neural Information Processing Systems, 457-464, 2009
1702009
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
1622011
Sharing features among dynamical systems with beta processes
E Fox, MI Jordan, EB Sudderth, AS Willsky
Advances in Neural Information Processing Systems, 549-557, 2009
1442009
Distributed occlusion reasoning for tracking with nonparametric belief propagation
EB Sudderth, MI Mandel, WT Freeman, AS Willsky
Advances in neural information processing systems, 1369-1376, 2005
1332005
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
1142012
Layered image motion with explicit occlusions, temporal consistency, and depth ordering
D Sun, EB Sudderth, MJ Black
Advances in Neural Information Processing Systems, 2226-2234, 2010
1122010
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
972004
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
942007
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
942004
Bayesian nonparametric methods for learning Markov switching processes
EB Fox, EB Sudderth, MI Jordan, AS Willsky
IEEE Signal Processing Magazine 27 (6), 43-54, 2010
852010
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