Ryan P. Adams

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Citazioni	45685	36807
Indice H	67	58
i10-index	131	115

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David DuvenaudAssociate Professor, University of TorontoEmail verificata su cs.toronto.edu
Hugo LarochelleGoogle DeepMind & MilaEmail verificata su google.com
Matthew J. JohnsonGoogle BrainEmail verificata su csail.mit.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleEmail verificata su eng.cam.ac.uk
Iain MurraySchool of Informatics, University of EdinburghEmail verificata su ed.ac.uk
Richard ZemelProfessor of Computer Science, University of TorontoEmail verificata su cs.toronto.edu
David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeEmail verificata su mrao.cam.ac.uk
Nando de FreitasCIFAR & DeepMindEmail verificata su google.com
Abigail G. DoyleUCLAEmail verificata su chem.ucla.edu
George E. DahlGoogle Inc.Email verificata su google.com
Peter OrbanzColumbia UniversityEmail verificata su stat.columbia.edu
Jamie KirosOpenAIEmail verificata su openai.com
Elaine AngelinoMiller Fellow, UC BerkeleyEmail verificata su eecs.berkeley.edu
Sigrid AdriaenssensPrinceton UniversityEmail verificata su princeton.edu
Emily B. FoxStanford UniversityEmail verificata su stanford.edu
Diana CaiCenter for Computational Mathematics, Flatiron InstituteEmail verificata su flatironinstitute.org
Margo SeltzerUniversity of British ColumbiaEmail verificata su cs.ubc.ca
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Hanna WallachPartner Research Manager, Microsoft ResearchEmail verificata su dirichlet.net
Joshua B. TenenbaumMITEmail verificata su mit.edu

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Ryan P. Adams

Princeton University

Email verificata su princeton.edu - Home page

Machine Learning Artificial Intelligence Statistics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Practical bayesian optimization of machine learning algorithms J Snoek, H Larochelle, RP Adams Advances in neural information processing systems 25, 2012	10738	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	5814	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	4500	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	3564	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	1342	2015
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	1187	2015
Gradient-based hyperparameter optimization through reversible learning D Maclaurin, D Duvenaud, R Adams International conference on machine learning, 2113-2122, 2015	1112	2015
Bayesian online changepoint detection RP Adams, DJC MacKay arXiv preprint arXiv:0710.3742, 2007	1107	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	1005	2016
Multi-task bayesian optimization K Swersky, J Snoek, RP Adams Advances in neural information processing systems 26, 2013	948	2013
Gaussian process kernels for pattern discovery and extrapolation A Wilson, R Adams International conference on machine learning, 1067-1075, 2013	833	2013
Mapping sub-second structure in mouse behavior AB Wiltschko, MJ Johnson, G Iurilli, RE Peterson, JM Katon, ... Neuron 88 (6), 1121-1135, 2015	748	2015
Bayesian optimization with unknown constraints MA Gelbart, J Snoek, RP Adams arXiv preprint arXiv:1403.5607, 2014	681	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	663	2021
Elliptical slice sampling I Murray, R Adams, D MacKay Proceedings of the thirteenth international conference on artificial …, 2010	568	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	561	2016
Spectral representations for convolutional neural networks O Rippel, J Snoek, RP Adams Advances in neural information processing systems 28, 2015	418	2015
Autograd: Effortless gradients in numpy D Maclaurin, D Duvenaud, RP Adams ICML 2015 AutoML workshop 238 (5), 2015	346	2015
Discovering latent network structure in point process data S Linderman, R Adams International conference on machine learning, 1413-1421, 2014	346	2014
Freeze-thaw Bayesian optimization K Swersky, J Snoek, RP Adams arXiv preprint arXiv:1406.3896, 2014	325	2014

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