Ryan P. Adams

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Citations	44084	35327
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David DuvenaudAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Hugo LarochelleGoogle DeepMind & MilaVerified email at google.com
Matthew J. JohnsonGoogle BrainVerified email at csail.mit.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Iain MurraySchool of Informatics, University of EdinburghVerified email at ed.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
Nando de FreitasCIFAR & DeepMindVerified email at google.com
George E. DahlGoogle Inc.Verified email at google.com
Abigail G. DoyleUCLAVerified email at chem.ucla.edu
Peter OrbanzColumbia UniversityVerified email at stat.columbia.edu
Jamie KirosOpenAIVerified email at openai.com
Elaine AngelinoMiller Fellow, UC BerkeleyVerified email at eecs.berkeley.edu
Emily B. FoxStanford UniversityVerified email at stanford.edu
Margo SeltzerUniversity of British ColumbiaVerified email at cs.ubc.ca
Diana CaiCenter for Computational Mathematics, Flatiron InstituteVerified email at flatironinstitute.org
Sigrid AdriaenssensPrinceton UniversityVerified email at princeton.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
Joshua B. TenenbaumMITVerified email at mit.edu

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	10344	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	5527	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	4384	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	3411	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	1311	2015
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	1146	2015
Bayesian online changepoint detection RP Adams, DJC MacKay arXiv preprint arXiv:0710.3742, 2007	1078	2007
Gradient-based hyperparameter optimization through reversible learning D Maclaurin, D Duvenaud, R Adams International conference on machine learning, 2113-2122, 2015	1071	2015
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	980	2016
Multi-task bayesian optimization K Swersky, J Snoek, RP Adams Advances in neural information processing systems 26, 2013	923	2013
Gaussian process kernels for pattern discovery and extrapolation A Wilson, R Adams International conference on machine learning, 1067-1075, 2013	811	2013
Mapping sub-second structure in mouse behavior AB Wiltschko, MJ Johnson, G Iurilli, RE Peterson, JM Katon, ... Neuron 88 (6), 1121-1135, 2015	716	2015
Bayesian optimization with unknown constraints MA Gelbart, J Snoek, RP Adams arXiv preprint arXiv:1403.5607, 2014	655	2014
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	613	2021
Elliptical slice sampling I Murray, R Adams, D MacKay Proceedings of the thirteenth international conference on artificial …, 2010	562	2010
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	552	2016
Spectral representations for convolutional neural networks O Rippel, J Snoek, RP Adams Advances in neural information processing systems 28, 2015	411	2015
Discovering latent network structure in point process data S Linderman, R Adams International conference on machine learning, 1413-1421, 2014	344	2014
Autograd: Effortless gradients in numpy D Maclaurin, D Duvenaud, RP Adams ICML 2015 AutoML workshop 238 (5), 2015	334	2015
Freeze-thaw Bayesian optimization K Swersky, J Snoek, RP Adams arXiv preprint arXiv:1406.3896, 2014	318	2014

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