Ryan P. Adams

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Citations	36748	31247
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David DuvenaudAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Hugo LarochelleGoogle Brain & MilaVerified email at google.com
Matthew J. JohnsonGoogle BrainVerified email at csail.mit.edu
Iain MurraySchool of Informatics, University of Edinburgh and AmazonVerified email at ed.ac.uk
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeVerified email at mrao.cam.ac.uk
Jennifer N WeiGoogleVerified email at google.com
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Li-wei H. LehmanMassachusetts Institute of TechnologyVerified email at mit.edu
George E. DahlGoogle Inc.Verified email at google.com
Abigail G. DoyleUCLAVerified email at chem.ucla.edu
Elaine AngelinoMiller Fellow, UC BerkeleyVerified email at eecs.berkeley.edu
Jamie KirosOpenAIVerified email at openai.com
Peter OrbanzColumbia UniversityVerified email at stat.columbia.edu
Emily B. FoxStanford UniversityVerified email at stanford.edu
Margo SeltzerUniversity of British ColumbiaVerified email at cs.ubc.ca
VICTORIA ABRAIRAAssistant Professor, Rutgers UniversityVerified email at scarletmail.rutgers.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Hanna WallachPartner Research Manager, Microsoft ResearchVerified email at dirichlet.net

Ryan P. Adams

Princeton University

Verified email at princeton.edu - Homepage

Machine Learning Artificial Intelligence Statistics


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 Advances in neural information processing systems 25, 2012	8400	2012
Taking the human out of the loop: A review of Bayesian optimization B Shahriari, K Swersky, Z Wang, RP Adams, N De Freitas Proceedings of the IEEE 104 (1), 148-175, 2015	4285	2015
Convolutional networks on graphs for learning molecular fingerprints DK Duvenaud, D Maclaurin, J Iparraguirre, R Bombarell, T Hirzel, ... Advances in neural information processing systems 28, 2015	3691	2015
Automatic chemical design using a data-driven continuous representation of molecules R Gómez-Bombarelli, JN Wei, D Duvenaud, JM Hernández-Lobato, ... ACS central science 4 (2), 268-276, 2018	2624	2018
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	1104	2015
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	979	2015
Gradient-based hyperparameter optimization through reversible learning D Maclaurin, D Duvenaud, R Adams International conference on machine learning, 2113-2122, 2015	917	2015
Bayesian online changepoint detection RP Adams, DJC MacKay arXiv preprint arXiv:0710.3742, 2007	907	2007
Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach R Gómez-Bombarelli, J Aguilera-Iparraguirre, TD Hirzel, D Duvenaud, ... Nature materials 15 (10), 1120-1127, 2016	811	2016
Multi-task bayesian optimization K Swersky, J Snoek, RP Adams Advances in neural information processing systems 26, 2013	784	2013
Gaussian process kernels for pattern discovery and extrapolation A Wilson, R Adams International conference on machine learning, 1067-1075, 2013	719	2013
Mapping sub-second structure in mouse behavior AB Wiltschko, MJ Johnson, G Iurilli, RE Peterson, JM Katon, ... Neuron 88 (6), 1121-1135, 2015	587	2015
Composing graphical models with neural networks for structured representations and fast inference MJ Johnson, DK Duvenaud, A Wiltschko, RP Adams, SR Datta Advances in neural information processing systems 29, 2016	511	2016
Bayesian optimization with unknown constraints MA Gelbart, J Snoek, RP Adams arXiv preprint arXiv:1403.5607, 2014	507	2014
Elliptical slice sampling I Murray, R Adams, D MacKay Proceedings of the thirteenth international conference on artificial …, 2010	505	2010
Bayesian reaction optimization as a tool for chemical synthesis BJ Shields, J Stevens, J Li, M Parasram, F Damani, JIM Alvarado, ... Nature 590 (7844), 89-96, 2021	366	2021
Advances in neural information processing systems J Snoek, H Larochelle, RP Adams, F Pereira, CJC Burges, L Bottou, ... Practical Bayesian optimization of machine learning algorithms, 2951-9, 2012	357	2012
Spectral representations for convolutional neural networks O Rippel, J Snoek, RP Adams Advances in neural information processing systems 28, 2015	345	2015
Discovering latent network structure in point process data S Linderman, R Adams International conference on machine learning, 1413-1421, 2014	327	2014
Freeze-thaw Bayesian optimization K Swersky, J Snoek, RP Adams arXiv preprint arXiv:1406.3896, 2014	276	2014

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