Ryan P. Adams

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Coauteurs

David DuvenaudAssociate Professor, University of TorontoAdresse e-mail validée de cs.toronto.edu
Hugo LarochelleGoogle Brain & MilaAdresse e-mail validée de google.com
Matthew J. JohnsonGoogle BrainAdresse e-mail validée de csail.mit.edu
Iain MurraySchool of Informatics, University of Edinburgh and AmazonAdresse e-mail validée de ed.ac.uk
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Richard ZemelProfessor of Computer Science, University of TorontoAdresse e-mail validée de cs.toronto.edu
David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeAdresse e-mail validée de mrao.cam.ac.uk
Jennifer N WeiGoogleAdresse e-mail validée de google.com
Nando de FreitasCIFAR & DeepMindAdresse e-mail validée de google.com
Li-wei H. LehmanMassachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
George E. DahlGoogle Inc.Adresse e-mail validée de google.com
Abigail G. DoyleUCLAAdresse e-mail validée de chem.ucla.edu
Elaine AngelinoMiller Fellow, UC BerkeleyAdresse e-mail validée de eecs.berkeley.edu
Jamie KirosOpenAIAdresse e-mail validée de openai.com
Peter OrbanzColumbia UniversityAdresse e-mail validée de stat.columbia.edu
Emily B. FoxStanford UniversityAdresse e-mail validée de stanford.edu
Margo SeltzerUniversity of British ColumbiaAdresse e-mail validée de cs.ubc.ca
VICTORIA ABRAIRAAssistant Professor, Rutgers UniversityAdresse e-mail validée de scarletmail.rutgers.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Hanna WallachPartner Research Manager, Microsoft ResearchAdresse e-mail validée de dirichlet.net

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Ryan P. Adams

Princeton University

Adresse e-mail validée de princeton.edu - Page d'accueil

Machine Learning Artificial Intelligence Statistics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Practical bayesian optimization of machine learning algorithms J Snoek, H Larochelle, RP Adams Advances in neural information processing systems 25, 2012	8414	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	4300	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	3695	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	2639	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	1108	2015
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	982	2015
Gradient-based hyperparameter optimization through reversible learning D Maclaurin, D Duvenaud, R Adams International conference on machine learning, 2113-2122, 2015	918	2015
Bayesian online changepoint detection RP Adams, DJC MacKay arXiv preprint arXiv:0710.3742, 2007	908	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	812	2016
Multi-task bayesian optimization K Swersky, J Snoek, RP Adams Advances in neural information processing systems 26, 2013	786	2013
Gaussian process kernels for pattern discovery and extrapolation A Wilson, R Adams International conference on machine learning, 1067-1075, 2013	722	2013
Mapping sub-second structure in mouse behavior AB Wiltschko, MJ Johnson, G Iurilli, RE Peterson, JM Katon, ... Neuron 88 (6), 1121-1135, 2015	591	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	511	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	369	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	358	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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