Erik B. Sudderth

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Alan S. WillskyProfessor of EECS, MITEmail verificata su mit.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Emily B. FoxUniversity of WashingtonEmail verificata su uw.edu
William T. FreemanProfessor of Computer Science, MITEmail verificata su mit.edu
Michael C. HughesAssistant Professor of Computer Science, Tufts UniversityEmail verificata su michaelchughes.com
Deqing SunResearch Scientist, GoogleEmail verificata su google.com
Antonio TorralbaProfessor of Computer Science, MITEmail verificata su csail.mit.edu
Michael J. BlackMax Planck Institute for Intelligent Systems and AmazonEmail verificata su tuebingen.mpg.de
Zhile RenApplied Research Scientist, AppleEmail verificata su apple.com
Alexander IhlerUniversity of California, IrvineEmail verificata su ics.uci.edu
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyEmail verificata su berkeley.edu
Stuart RussellProfessor of Computer Science, University of California, BerkeleyEmail verificata su cs.berkeley.edu
Dae Il KimBrown UniversityEmail verificata su cs.brown.edu
Soumya GhoshBrown UniversityEmail verificata su cs.brown.edu
Hanspeter PfisterAn Wang Professor of Computer Science, Harvard UniversityEmail verificata su seas.harvard.edu
Michael I MandelAssociate Professor of Computer and Information Science at Brooklyn College, CUNYEmail verificata su sci.brooklyn.cuny.edu
Michael IsardResearch Scientist, GoogleEmail verificata su google.com
Jyri J. KivinenGE HealthcareEmail verificata su ge.com
David BleiProfessor of Statistics and Computer Science, Columbia UniversityEmail verificata su columbia.edu
Finale DoshiAssistant Professor, HarvardEmail verificata su seas.harvard.edu

Erik B. Sudderth

Professor of Computer Science, UC Irvine

Email verificata su uci.edu - Home page

Machine Learning Computer Vision Statistics Bayesian Nonparametrics Signal Processing


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Nonparametric belief propagation and facial appearance estimation EB Sudderth, AT Ihler, WT Freeman, AS Willsky	809*	2002
Nonparametric belief propagation EB Sudderth, AT Ihler, WT Freeman, AS Willsky IEEE Conference on Computer Vision & Pattern Recognition, 605-612, 2003	572*	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	466*	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	413	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	324	2008
Nonparametric belief propagation EB Sudderth, AT Ihler, M Isard, WT Freeman, AS Willsky Communications of the ACM 53 (10), 95-103, 2010	300	2010
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	228	2008
Graphical models for visual object recognition and tracking EB Sudderth Massachusetts Institute of Technology, 2006	226	2006
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	225	2004
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	214	2011
Shared segmentation of natural scenes using dependent Pitman-Yor processes E Sudderth, M Jordan Advances in neural information processing systems 21, 1585-1592, 2008	208	2008
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	207	2008
Describing visual scenes using transformed dirichlet processes A Torralba, AS Willsky, EB Sudderth, WT Freeman Advances in neural information processing systems, 1297-1304, 2006	188	2006
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	161	2009
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	131	2010
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	131	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	125	2012
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	105	2004
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	102	2004
Truly nonparametric online variational inference for hierarchical Dirichlet processes M Bryant, E Sudderth Advances in Neural Information Processing Systems 25, 2699-2707, 2012	99	2012

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