Roman Garnett

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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
Kristian KerstingProfessor of Artificial Intelligence and Machine Learning, hessian.ai, TU Darmstadt, GermanyVerified email at cs.tu-darmstadt.de
Gustavo MalkomesIntelVerified email at intel.com
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
Benjamin MoseleyCarnegie Mellon UniversityVerified email at andrew.cmu.edu
David SumpterProfessor of Applied Mathematics, Uppsala UniversityVerified email at math.uu.se
Ashley WardUniversity of SydneyVerified email at sydney.edu.au
Christian BauckhageProf. of Computer Science, University of Bonn, Fraunhofer IAISVerified email at bit.uni-bonn.de
Henry ChaiWashington University in Saint LouisVerified email at wustl.edu

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	682	2005
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts 3rd international conference on learning and intelligent optimization (LION3 …, 2009	267	2009
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE international conference on information …, 2010	150	2010
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine Learning 102 (2), 209-245, 2016	119	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, 46-54, 2012	100	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	95	2012
Sampling for inference in probabilistic models with fast Bayesian quadrature T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts arXiv preprint arXiv:1411.0439, 2014	75	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	74	2010
Active learning of linear embeddings for Gaussian processes R Garnett, MA Osborne, P Hennig arXiv preprint arXiv:1310.6740, 2013	69	2013
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	63	2013
Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Workshop on Automatic Machine Learning, 41-47, 2016	62	2016
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
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
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	45	2017
Active search on graphs X Wang, R Garnett, J Schneider Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	44	2013
D-vae: A variational autoencoder for directed acyclic graphs M Zhang, S Jiang, Z Cui, R Garnett, Y Chen arXiv preprint arXiv:1904.11088, 2019	41	2019
Differentially private Bayesian optimization M Kusner, J Gardner, R Garnett, K Weinberger International conference on machine learning, 918-927, 2015	40	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	39	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	38	2011
Bioinspired polarization vision enables underwater geolocalization SB Powell, R Garnett, J Marshall, C Rizk, V Gruev Science advances 4 (4), eaao6841, 2018	37	2018

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