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
Gustavo MalkomesIntelVerified email at intel.com
Kristian KerstingProfessor of AI & ML, Technical University of Darmstadt, Co-Director hessian.ai, DFKI, CAIRNE, ELLISVerified email at cs.tu-darmstadt.de
Shali JiangFacebookVerified email at wustl.edu
Richard P MannProfessor of Mathematical Ecology & Evolution, University of LeedsVerified email at leeds.ac.uk
Marion NeumannWashington University in St. LouisVerified email at wustl.edu
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Quan NguyenPostdoc, Princeton UniversityVerified email at wustl.edu
Alvitta OttleyWashington University in St. LouisVerified email at wustl.edu
Simeon BirdUniversity of California, RiversideVerified email at ucr.edu
Thomas GärtnerTU Wien (Technical University of Vienna)Verified email at tuwien.ac.at
Wenjie HeAssociate Professor, University of Missouri -St. LouisVerified email at umsl.edu
Tim HuegerichSenior Economist, L. R. Christensen AssociatesVerified email at uwalumni.com
Yifei MaApplied Scientist, Amazon.ComVerified email at amazon.com
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
Benjamin MoseleyCarnegie Mellon UniversityVerified email at andrew.cmu.edu
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	841	2005
Bayesian Optimization R Garnett	738	2023
Gaussian processes for global optimization MA Osborne, R Garnett, SJ Roberts	368	2009
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine learning 102, 209-245, 2016	306	2016
Bayesian optimization for sensor set selection R Garnett, MA Osborne, SJ Roberts Proceedings of the 9th ACM/IEEE international conference on information …, 2010	221	2010
D-VAE: A variational autoencoder for directed acyclic graphs M Zhang, S Jiang, Z Cui, R Garnett, Y Chen Advances in Neural Information Processing Systems 32, 2019	218	2019
Bioinspired polarization vision enables underwater geolocalization SB Powell, R Garnett, J Marshall, C Rizk, V Gruev Science advances 4 (4), eaao6841, 2018	159	2018
Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Advances in Neural Information Processing Systems 29, 2016	152	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, 2012	145	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	144	2012
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	133	2017
Active learning of linear embeddings for Gaussian processes R Garnett, MA Osborne, P Hennig arXiv preprint arXiv:1310.6740, 2013	127	2013
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, 2014	124	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	96	2010
Σ-optimality for active learning on gaussian random fields Y Ma, R Garnett, J Schneider Advances in Neural Information Processing Systems, 2751-2759, 2013	74	2013
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	70	2009
Differentially private Bayesian optimization M Kusner, J Gardner, R Garnett, K Weinberger International conference on machine learning, 918-927, 2015	69	2015
Efficient graph kernels by randomization M Neumann, N Patricia, R Garnett, K Kersting Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012	68	2012
Efficient nonmyopic active search S Jiang, G Malkomes, G Converse, A Shofner, B Moseley, R Garnett International Conference on Machine Learning, 1714-1723, 2017	62	2017
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	62	2017

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