Jasper Snoek

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	All	Since 2016
Citations	8298	7500
h-index	25	23
i10-index	32	29

2600

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650

1950

201220132014201520162017201820192020202130 95 201 341 624 904 1377 1909 2582 95

Co-authors

Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Hugo LarochelleGoogle Brain & MilaVerified email at google.com
Kevin SwerskyGoogle BrainVerified email at cs.toronto.edu
Alex MihailidisProfessor, Department of Occupational Science & Occupational Therapy, University of TorontoVerified email at utoronto.ca
Babak TaatiScientist & Assistant Professor, KITE | Toronto Rehab - UHN & University of TorontoVerified email at uhn.ca
Oren RippelMIT, Harvard UniversityVerified email at mit.edu
David R KelleyCalico LabsVerified email at calicolabs.com
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
PrabhatLawrence Berkeley National Lab; UC BerkeleyVerified email at lbl.gov
Kevin Leyton-BrownProfessor of Computer Science, University of British Columbia; Canada CIFAR AI Chair, AmiiVerified email at cs.ubc.ca
James BergstraVerified email at uwaterloo.ca
Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Michael (Mike) GelbartUniversity of British ColumbiaVerified email at cs.ubc.ca
Jesse HoeyProfessor of Computer Science, University of WaterlooVerified email at cs.uwaterloo.ca
David DuvenaudAssistant Professor, University of TorontoVerified email at cs.toronto.edu
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Shamim NematiUCSDVerified email at ucsd.edu
Ahmad AklPhD Candidate, University of TorontoVerified email at utoronto.ca
Mohammad Mahdi GhassemiMichigan State UniversityVerified email at msu.edu

Jasper Snoek

Google Brain

Verified email at google.com

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Practical bayesian optimization of machine learning algorithms J Snoek, H Larochelle, RP Adams arXiv preprint arXiv:1206.2944, 2012	4287	2012
Scalable bayesian optimization using deep neural networks J Snoek, O Rippel, K Swersky, R Kiros, N Satish, N Sundaram, M Patwary, ... International conference on machine learning, 2171-2180, 2015	565	2015
Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks DR Kelley, J Snoek, JL Rinn Genome research 26 (7), 990-999, 2016	516	2016
Multi-task bayesian optimization K Swersky, J Snoek, RP Adams Curran Associates, Inc., 2013	459	2013
Towards an empirical foundation for assessing bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... NIPS workshop on Bayesian Optimization in Theory and Practice 10, 3, 2013	243	2013
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, JV Dillon, ... arXiv preprint arXiv:1906.02530, 2019	241	2019
Bayesian optimization with unknown constraints MA Gelbart, J Snoek, RP Adams arXiv preprint arXiv:1403.5607, 2014	237	2014
Spectral representations for convolutional neural networks O Rippel, J Snoek, RP Adams arXiv preprint arXiv:1506.03767, 2015	203	2015
Freeze-thaw bayesian optimization K Swersky, J Snoek, RP Adams arXiv preprint arXiv:1406.3896, 2014	167	2014
Input warping for bayesian optimization of non-stationary functions J Snoek, K Swersky, R Zemel, R Adams International Conference on Machine Learning, 1674-1682, 2014	166	2014
Deep bayesian bandits showdown: An empirical comparison of bayesian deep networks for thompson sampling C Riquelme, G Tucker, J Snoek arXiv preprint arXiv:1802.09127, 2018	122	2018
Sequential regulatory activity prediction across chromosomes with convolutional neural networks DR Kelley, YA Reshef, M Bileschi, D Belanger, CY McLean, J Snoek Genome research 28 (5), 739-750, 2018	107	2018
Likelihood ratios for out-of-distribution detection J Ren, PJ Liu, E Fertig, J Snoek, R Poplin, MA DePristo, JV Dillon, ... arXiv preprint arXiv:1906.02845, 2019	94	2019
Winner's curse? On pace, progress, and empirical rigor D Sculley, J Snoek, A Wiltschko, A Rahimi	87	2018
Automated detection of unusual events on stairs J Snoek, J Hoey, L Stewart, RS Zemel, A Mihailidis Image and Vision Computing 27 (1-2), 153-166, 2009	81	2009
Learning latent permutations with gumbel-sinkhorn networks G Mena, D Belanger, S Linderman, J Snoek arXiv preprint arXiv:1802.08665, 2018	75	2018
Towards a single sensor passive solution for automated fall detection M Belshaw, B Taati, J Snoek, A Mihailidis 2011 Annual International Conference of the IEEE Engineering in Medicine and …, 2011	61	2011
Raiders of the lost architecture: Kernels for Bayesian optimization in conditional parameter spaces K Swersky, D Duvenaud, J Snoek, F Hutter, MA Osborne arXiv preprint arXiv:1409.4011, 2014	58	2014
Nonparametric guidance of autoencoder representations using label information J Snoek, RP Adams, H Larochelle Journal of Machine Learning Research, 2012	57	2012
Machine learning approaches in cardiovascular imaging M Henglin, G Stein, PV Hushcha, J Snoek, AB Wiltschko, S Cheng Circulation: Cardiovascular Imaging 10 (10), e005614, 2017	54	2017

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