Erik B. Sudderth

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Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Emily B. FoxUniversity of WashingtonVerified email at uw.edu
William T. FreemanProfessor of Computer Science, MITVerified email at mit.edu
Michael C. HughesAssistant Professor of Computer Science, Tufts UniversityVerified email at michaelchughes.com
Deqing SunResearch Scientist, GoogleVerified email at google.com
Antonio TorralbaProfessor of Computer Science, MITVerified email at csail.mit.edu
Michael J. BlackMax Planck Institute for Intelligent Systems and AmazonVerified email at tuebingen.mpg.de
Zhile RenApplied Research Scientist, AppleVerified email at apple.com
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyVerified email at berkeley.edu
Alexander IhlerUniversity of California, IrvineVerified email at ics.uci.edu
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Dae Il KimBrown UniversityVerified email at cs.brown.edu
Michael I MandelAssociate Professor of Computer and Information Science at Brooklyn College, CUNYVerified email at sci.brooklyn.cuny.edu
Soumya GhoshMIT-IBM Watson AI Lab, IBM ResearchVerified email at cs.brown.edu
Michael IsardResearch Scientist, GoogleVerified email at google.com
Hanspeter PfisterAn Wang Professor of Computer Science, Harvard UniversityVerified email at seas.harvard.edu
Jyri J. KivinenLapland University of Applied SciencesVerified email at lapinamk.fi
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Jan KautzVice President of Research, NVIDIA ResearchVerified email at nvidia.com

Erik B. Sudderth

Professor of Computer Science, UC Irvine

Verified email at uci.edu - Homepage

Machine Learning Computer Vision Statistics Bayesian Nonparametrics Signal Processing


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Nonparametric belief propagation EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky Communications of the ACM 53 (10), 95-103, 2010	824*	2010
Nonparametric belief propagation EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky Communications of the ACM 53 (10), 95-103, 2010	745	2010
Nonparametric belief propagation EB Sudderth, AT Ihler, WT Freeman, AS Willsky IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003	745*	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	483*	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	419	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	322	2008
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	235	2008
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	235	2004
Graphical models for visual object recognition and tracking EB Sudderth Massachusetts Institute of Technology, 2006	232	2006
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	223	2011
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	217	2008
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes. EB Sudderth, MI Jordan NIPS, 1585-1592, 2008	213	2008
Describing visual scenes using transformed dirichlet processes E Sudderth, A Torralba, W Freeman, A Willsky NIPS 18, 1297-1304, 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, 549-557, 2009	164	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, 2226-2234, 2010	142	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, 2226-2234, 2010	142	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	133	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	109	2016
Efficient multiscale sampling from products of Gaussian mixtures AT Ihler, EB Sudderth, WT Freeman, AS Willsky Advances in Neural Information Processing Systems 16, 1-8, 2004	109	2004
Truly nonparametric online variational inference for hierarchical Dirichlet processes M Bryant, E Sudderth Advances in Neural Information Processing Systems 25, 2699-2707, 2012	104	2012

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