Christian R. Shelton

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Daphne KollerCEO and Founder, insitroVerified email at insitro.com
Eamonn KeoghDistinguished Professor of Computer Science, University of California - RiversideVerified email at cs.ucr.edu
Zhen QinGoogle DeepMindVerified email at google.com
Suresh VenkatasubramanianBrown UniversityVerified email at brown.edu
Lydia E. KavrakiRice UniversityVerified email at rice.edu
Dan HalperinProfessor of Computer Science, Tel Aviv UniversityVerified email at tauex.tau.ac.il
TOMASO POGGIOMcDermott Professor in Brain Sciences, MITVerified email at ai.mit.edu
Paul William FinnOxford Drug Design Limited, University of Buckingham, Affinity Drug DesignVerified email at oxforddrugdesign.com
Thomas GirkeProfessor of BioinformaticsVerified email at ucr.edu
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Michael KearnsProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Satinder SinghGoogle DeepMind / U. of MichiganVerified email at umich.edu
Chotirat Ann RatanamahatanaAssociate Professor, Dept. of Computer Engineering, Chulalongkorn UniversityVerified email at chula.ac.th
Mike IzbickiClaremont McKenna CollegeVerified email at izbicki.me
Bryan M. WongUniversity of California, RiversideVerified email at alum.mit.edu
Victor ZordanProfessor of Computer Science, Clemson UniversityVerified email at g.clemson.edu
E. Busra CelikkayaAmazonVerified email at amazon.com
Antony LamMercari, Inc.Verified email at mercari.com
Julia Bailey-SerresCenter for Plant Cell Biology, UC RiversideVerified email at ucr.edu
John CushmanUniversity of NevadaVerified email at unr.edu

Christian R. Shelton

Professor, University of California, Riverside

Verified email at cs.ucr.edu - Homepage

machine learning point processes artificial intelligence graphical models


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Fast time series classification using numerosity reduction X Xi, E Keogh, C Shelton, L Wei, CA Ratanamahatana Proceedings of the 23rd international conference on Machine learning, 1033-1040, 2006	728	2006
Continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2002	393*	2002
Momentum control for balance A Macchietto, V Zordan, CR Shelton ACM SIGGRAPH 2009 papers, 1-8, 2009	274	2009
A social reinforcement learning agent C Isbell, CR Shelton, M Kearns, S Singh, P Stone Proceedings of the fifth international conference on Autonomous agents, 377-384, 2001	226	2001
Annotating genes of known and unknown function by large-scale coexpression analysis K Horan, C Jang, J Bailey-Serres, R Mittler, C Shelton, JF Harper, JK Zhu, ... Plant physiology 147 (1), 41-57, 2008	212	2008
Automated, highly-accurate, bug assignment using machine learning and tossing graphs P Bhattacharya, I Neamtiu, CR Shelton Journal of Systems and Software 85 (10), 2275-2292, 2012	191	2012
Learning continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2003	187*	2003
Improving Multi-target Tracking via Social Grouping Z Qin, CR Shelton IEEE Conference on Computer Vision and Pattern Recognition, 2012	181	2012
Cobot in LambdaMOO: An adaptive social statistics agent CL Isbell, M Kearns, S Singh, CR Shelton, P Stone, D Kormann Autonomous Agents and Multi-Agent Systems 13, 327-354, 2006	154	2006
Morphable surface models CR Shelton International Journal of Computer Vision 38, 75-91, 2000	140	2000
A perturbation scheme for spherical arrangements with application to molecular modeling D Halperin, CR Shelton Proceedings of the thirteenth annual symposium on Computational geometry …, 1997	123	1997
A continuation method for Nash equilibria in structured games B Blum, CR Shelton, D Koller Journal of Artificial Intelligence Research 25, 457-502, 2006	114	2006
An electronic market-maker NT Chan, C Shelton	109	2001
Intrusion detection using continuous time Bayesian networks J Xu, CR Shelton Journal of Artificial Intelligence Research 39, 745-774, 2010	108	2010
Expectation maximization and complex duration distributions for continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2005	106*	2005
Importance sampling for reinforcement learning with multiple objectives CR Shelton	105	2001
Machine learning, machine vision, and the brain T Poggio, CR Shelton AI Magazine 20 (3), 37-37, 1999	100	1999
Learning from scarce experience L Peshkin, CR Shelton International Conference on Machine Learning, 2002	96	2002
Rapid: Randomized pharmacophore identification for drug design PW Finn, LE Kavraki, JC Latombe, R Motwani, C Shelton, ... Proceedings of the thirteenth annual symposium on Computational geometry …, 1997	96	1997
Expectation propagation for continuous time Bayesian networks U Nodelman, D Koller, CR Shelton Uncertainty in Artificial Intelligence, 2005	92*	2005

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