Michael U. Gutmann

Cited by

	All	Since 2016
Citations	2751	2416
h-index	21	18
i10-index	31	28

920

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200620072008200920102011201220132014201520162017201820192020202110 5 8 13 13 10 24 48 75 101 203 268 449 556 901 31

Co-authors

Aapo HyvarinenUniversity of HelsinkiVerified email at helsinki.fi
Jarno LintusaariAalto UniversityVerified email at aalto.fi
William HanageHarvard T H Chan School of Public HealthVerified email at hsph.harvard.edu
Aki VehtariAssociate Professor, Aalto UniversityVerified email at aalto.fi
Marko JärvenpääResearcher, University of OsloVerified email at medisin.uio.no
Charles SuttonGoogle, University of EdinburghVerified email at inf.ed.ac.uk
Akash SrivastavaMIT, IBM Research, University of EdinburghVerified email at mit.edu
Marc LipsitchDepartment of Epidemiology, Harvard School of Public HealthVerified email at hsph.harvard.edu
Brian J ArnoldHarvard UniversityVerified email at g.harvard.edu
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
John QuinnGoogle AI Ghana, Makerere UniversityVerified email at cit.ac.ug
Song LiuLecturer in Statistical Science, University of Bristol, UKVerified email at bristol.ac.uk
Nick CroucherImperial CollegeVerified email at imperial.ac.uk
Shouno HayaruUniversity of Electro-CommunicationsVerified email at uec.ac.jp
Kartic SubrUniversity of EdinburghVerified email at ed.ac.uk
Subramanian RamamoorthyProfessor of Robot Learning and Autonomy, School of Informatics, University of EdinburghVerified email at ed.ac.uk
Samuel K. SheppardThe Milner Centre for Evolution, University of Bath, United KingdomVerified email at bath.ac.uk
Jesus MaloProfessor of Vision Science, Universitat de ValenciaVerified email at uv.es
Valero LaparraUniversitat de ValènciaVerified email at uv.es
Christophe FraserOxford Big Data Institute, Nuffield Department of Medicine, University of OxfordVerified email at bdi.ox.ac.uk

Michael U. Gutmann

University of Edinburgh

Verified email at ed.ac.uk - Homepage

Machine Learning Bayesian Computation Computational Biology


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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models M Gutmann, A Hyvärinen Proceedings of the Thirteenth International Conference on Artificial …, 2010	714	2010
Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics MU Gutmann, A Hyvärinen The journal of machine learning research 13 (1), 307-361, 2012	543	2012
Veegan: Reducing mode collapse in gans using implicit variational learning A Srivastava, L Valkov, C Russell, MU Gutmann, C Sutton Advances in neural information processing systems, 3308-3318, 2017	274	2017
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models MU Gutmann, J Corander Journal of Machine Learning Research 17, 1-47, 2016	184	2016
Fundamentals and recent developments in approximate Bayesian computation J Lintusaari, MU Gutmann, R Dutta, S Kaski, J Corander Systematic biology 66 (1), e66-e82, 2017	151	2017
Likelihood-free inference via classification MU Gutmann, R Dutta, S Kaski, J Corander Statistics and Computing 28 (2), 411-425, 2018	90*	2018
Frequency-dependent selection in vaccine-associated pneumococcal population dynamics J Corander, C Fraser, MU Gutmann, B Arnold, WP Hanage, SD Bentley, ... Nature ecology & evolution 1 (12), 1950-1960, 2017	76	2017
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2 A Hyvärinen, M Gutmann, PO Hoyer BMC neuroscience 6 (1), 1-12, 2005	48	2005
Likelihood-free inference by ratio estimation O Thomas, R Dutta, J Corander, S Kaski, MU Gutmann Bayesian Analysis, 2020	44*	2020
Bregman divergence as general framework to estimate unnormalized statistical models M Gutmann, J Hirayama arXiv preprint arXiv:1202.3727, 2012	43	2012
Recombination produces coherent bacterial species clusters in both core and accessory genomes P Marttinen, NJ Croucher, MU Gutmann, J Corander, WP Hanage Microbial Genomics 1 (5), 2015	41	2015
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation S Liu, JA Quinn, MU Gutmann, M Sugiyama European Conference on Machine Learning and Principles and Practice of …, 2013	39	2013
Elfi: Engine for likelihood-free inference J Lintusaari, H Vuollekoski, A Kangasrääsiö, K Skytén, M Järvenpää, ... The Journal of Machine Learning Research 19 (1), 643-649, 2018	38*	2018
Bayesian inference of atomistic structure in functional materials M Todorović, MU Gutmann, J Corander, P Rinke Npj computational materials 5 (1), 1-7, 2019	37	2019
Efficient acquisition rules for model-based approximate Bayesian computation M Järvenpää, MU Gutmann, A Pleska, A Vehtari, P Marttinen Bayesian Analysis 14 (2), 595-622, 2019	34	2019
A family of computationally efficient and simple estimators for unnormalized statistical models M Pihlaja, M Gutmann, A Hyvarinen arXiv preprint arXiv:1203.3506, 2012	32	2012
Genome-wide CRISPR screen identifies host dependency factors for influenza A virus infection B Li, SM Clohisey, BS Chia, B Wang, A Cui, T Eisenhaure, LD Schweitzer, ... Nature communications 11 (1), 1-18, 2020	31	2020
Weak epistasis may drive adaptation in recombining bacteria BJ Arnold, MU Gutmann, YH Grad, SK Sheppard, J Corander, M Lipsitch, ... Genetics 208 (3), 1247-1260, 2018	30	2018
Statistical models of images and early vision M Gutmann	22	2005
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images MU Gutmann, V Laparra, A Hyvärinen, J Malo PloS one 9 (2), e86481, 2014	21	2014

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