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Erik B. Sudderth
Erik B. Sudderth
Professor of Computer Science, UC Irvine
Zweryfikowany adres z uci.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
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
621*2011
Nonparametric belief propagation
EB Sudderth, AT Ihler, WT Freeman, AS Willsky
IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003
595*2003
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
4412005
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
3812008
Nonparametric belief propagation
EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky
Communications of the ACM 53 (10), 95-103, 2010
3452010
Nonparametric Bayesian learning of switching linear dynamical systems
E Fox, E Sudderth, M Jordan, A Willsky
Advances in neural information processing systems 21, 2008
3002008
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
2932011
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
2622004
Graphical models for visual object recognition and tracking
EB Sudderth
Massachusetts Institute of Technology, 2006
2572006
Describing visual scenes using transformed objects and parts
EB Sudderth, A Torralba, WT Freeman, AS Willsky
International Journal of Computer Vision 77, 291-330, 2008
2442008
Shared segmentation of natural scenes using dependent Pitman-Yor processes
E Sudderth, M Jordan
Advances in neural information processing systems 21, 2008
2282008
Sharing features among dynamical systems with beta processes
E Fox, M Jordan, E Sudderth, A Willsky
Advances in neural information processing systems 22, 2009
1862009
Describing visual scenes using transformed dirichlet processes
A Torralba, A Willsky, E Sudderth, W Freeman
Advances in neural information processing systems 18, 2005
1832005
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
1772016
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
1612010
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
1572012
Memoized online variational inference for Dirichlet process mixture models
MC Hughes, E Sudderth
Advances in neural information processing systems 26, 2013
1372013
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, 1281-1313, 2014
1352014
A fully-connected layered model of foreground and background flow
D Sun, J Wulff, EB Sudderth, H Pfister, MJ Black
Proceedings of the IEEE conference on computer vision and pattern …, 2013
1212013
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
1182010
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