Roman Garnett

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	All	Since 2016
Citations	2690	1778
h-index	24	23
i10-index	47	44

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Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerified email at robots.ox.ac.uk
Jeff SchneiderCarnegie Mellon UniversityVerified email at cs.cmu.edu
Richard P MannSchool of Mathematics, University of LeedsVerified email at leeds.ac.uk
Gustavo MalkomesSigOptVerified email at sigopt.com
Kristian KerstingProfessor of Artificial Intelligence and Machine Learning, hessian.ai, TU DarmstadtVerified email at cs.tu-darmstadt.de
Marion NeumannWashington University in St. LouisVerified email at wustl.edu
Shali JiangFacebookVerified email at wustl.edu
Wenjie HeAssociate Professor, University of Missouri -St. LouisVerified email at umsl.edu
Thomas GärtnerTU Wien (Technical University of Vienna)Verified email at tuwien.ac.at
Yifei MaApplied Scientist, Amazon.ComVerified email at amazon.com
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Shirley HoFlatiron Institute, Center for Computational AstrophysicsVerified email at flatironinstitute.org
James Herbert-ReadDepartment of Zoology, University of CambridgeVerified email at cam.ac.uk
Andrea PernaLife Sciences, University of RoehamptonVerified email at perna.fr
David SumpterProfessor of Applied Mathematics, Uppsala UniversityVerified email at math.uu.se
Henry ChaiWashington University in Saint LouisVerified email at wustl.edu
Dennis BarbourAssociate Professor of Biomedical EngineeringVerified email at opayq.com

Roman Garnett

Washington University in St. Louis

Verified email at wustl.edu - Homepage

machine learning active learning active search Bayesian optimization Gaussian processes


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A universal noise removal algorithm with an impulse detector R Garnett, T Huegerich, C Chui, W He IEEE Transactions on image processing 14 (11), 1747-1754, 2005	664	2005
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd international conference on learning and intelligent optimization (LION3 …, 2009	261	2009
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE international conference on information …, 2010	142	2010
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine Learning 102 (2), 209-245, 2016	109	2016
Active learning of model evidence using Bayesian quadrature M Osborne, R Garnett, Z Ghahramani, DK Duvenaud, SJ Roberts, ... Advances in neural information processing systems 25, 46-54, 2012	99	2012
Bayesian optimal active search and surveying R Garnett, Y Krishnamurthy, X Xiong, J Schneider, R Mann International Conference on Machine Learning (ICML 2012), 2012	93	2012
Sampling for inference in probabilistic models with fast Bayesian quadrature T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts Advances in neural information processing systems 27, 2789-2797, 2014	74	2014
Sequential Bayesian prediction in the presence of changepoints and faults R Garnett, MA Osborne, S Reece, A Rogers, SJ Roberts The Computer Journal 53 (9), 1430-1446, 2010	72	2010
Multi-scale inference of interaction rules in animal groups using Bayesian model selection RP Mann, A Perna, D Strömbom, R Garnett, JE Herbert-Read, ... PLoS Comput Biol 9 (3), e1002961, 2013	66	2013
Active learning of linear embeddings for Gaussian processes R Garnett, MA Osborne, P Hennig arXiv preprint arXiv:1310.6740, 2013	65	2013
Efficient graph kernels by randomization M Neumann, N Patricia, R Garnett, K Kersting Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012	61	2012
Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Workshop on Automatic Machine Learning, 41-47, 2016	57	2016
Sequential Bayesian prediction in the presence of changepoints R Garnett, MA Osborne, SJ Roberts Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	57	2009
Active search on graphs X Wang, R Garnett, J Schneider Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	44	2013
Discovering and exploiting additive structure for Bayesian optimization J Gardner, C Guo, K Weinberger, R Garnett, R Grosse Artificial Intelligence and Statistics, 1311-1319, 2017	43	2017
Differentially private Bayesian optimization M Kusner, J Gardner, R Garnett, K Weinberger International conference on machine learning, 918-927, 2015	38	2015
Σ-optimality for active learning on gaussian random fields Y Ma, R Garnett, J Schneider Advances in Neural Information Processing Systems, 2751-2759, 2013	38	2013
Objectively identifying landmark use and predicting flight trajectories of the homing pigeon using Gaussian processes R Mann, R Freeman, M Osborne, R Garnett, C Armstrong, J Meade, ... Journal of The Royal Society Interface 8 (55), 210-219, 2011	37	2011
Power iterated color refinement K Kersting, M Mladenov, R Garnett, M Grohe Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014	36	2014
Statistical properties of damped Lyman-alpha systems from Sloan Digital Sky Survey DR12 S Bird, R Garnett, S Ho Monthly Notices of the Royal Astronomical Society 466 (2), 2111-2122, 2017	33	2017

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