José Miguel Hernández-Lobato - Google Scholar Citations

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	All	Since 2014
Citations	3262	3154
h-index	27	26
i10-index	49	44

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Daniel Hernández-LobatoLecturer of Computer Science, Unviersidad Autónoma de MadridVerified email at uam.es
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Richard E TurnerUniversity Reader, University of CambridgeVerified email at cam.ac.uk
Yingzhen LiMicrosoft Research CambridgeVerified email at cam.ac.uk
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Verified email at utoronto.ca
Neil HoulsbyGoogleVerified email at google.com
Matt J. KusnerAssociate Professor, University College LondonVerified email at ucl.ac.uk
Alberto SuárezProfessor of Artificial Intelligence, Computer Science Department, Universidad Autónoma de MadridVerified email at uam.es
Thang D BuiResearch Scientist, Uber AI; Lecturer, University of SydneyVerified email at sydney.edu.au
Brooks PaigeAssociate Professor, University College LondonVerified email at ucl.ac.uk
Matthew W. HoffmanUniversity of CambridgeVerified email at cam.ac.uk
Brandon ReagenResearch Scientist, FacebookVerified email at fb.com
David BrooksHaley Family Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Bob AdolfGraduate Student, Harvard UniversityVerified email at seas.harvard.edu
Gu-Yeon WeiProfessor of EE and CS, Harvard UniversityVerified email at eecs.harvard.edu
Paul N WhatmoughArm Research, Harvard UniversityVerified email at seas.harvard.edu
Rafael Gómez-BombarelliAssistant Professor, MIT DMSEVerified email at mit.edu
Jorge Aguilera-IparraguirreRecursion PharmaceuticalsVerified email at recursionpharma.com
David DuvenaudAssistant Professor, University of TorontoVerified email at cs.toronto.edu

José Miguel Hernández-Lobato

University Lecturer (US Assistant Professor) University of Cambridge

Verified email at cam.ac.uk - Homepage

Bayesian Optimization Bayesian Neural Networks Conditional Copulas Bayesian Sparsity Approximate Inference


Title	Cited by	Year
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	516	2018
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International Conference on Machine Learning, 1861-1869, 2015	328	2015
Minerva: Enabling low-power, highly-accurate deep neural network accelerators B Reagen, P Whatmough, R Adolf, S Rama, H Lee, SK Lee, ... 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture …, 2016	278	2016
Predictive entropy search for efficient global optimization of black-box functions JM Hernández-Lobato, MW Hoffman, Z Ghahramani Advances in neural information processing systems, 918-926, 2014	245	2014
Grammar variational autoencoder MJ Kusner, B Paige, JM Hernández-Lobato Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	174	2017
Gans for sequences of discrete elements with the gumbel-softmax distribution MJ Kusner, JM Hernández-Lobato arXiv preprint arXiv:1611.04051, 2016	117	2016
Deep Gaussian processes for regression using approximate expectation propagation T Bui, D Hernández-Lobato, J Hernandez-Lobato, Y Li, R Turner International Conference on Machine Learning, 1472-1481, 2016	109	2016
Black-box α-divergence minimization JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ... International Machine Learning Society, 2016	95	2016
Collaborative Gaussian processes for preference learning N Houlsby, F Huszar, Z Ghahramani, JM Hernández-Lobato Advances in neural information processing systems, 2096-2104, 2012	89	2012
Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation D Hernández-Lobato, JM Hernández-Lobato, P Dupont The Journal of Machine Learning Research 14 (1), 1891-1945, 2013	85	2013
Learning and policy search in stochastic dynamical systems with bayesian neural networks S Depeweg, JM Hernández-Lobato, F Doshi-Velez, S Udluft arXiv preprint arXiv:1605.07127, 2016	71	2016
Stochastic expectation propagation Y Li, JM Hernández-Lobato, RE Turner Advances in neural information processing systems, 2323-2331, 2015	68	2015
Probabilistic matrix factorization with non-random missing data JM Hernández-Lobato, N Houlsby, Z Ghahramani International Conference on Machine Learning, 1512-1520, 2014	59	2014
Predictive entropy search for bayesian optimization with unknown constraints JM Hernández-Lobato, MA Gelbart, MW Hoffman, RP Adams, ... JMLR, 2015	56	2015
Predictive entropy search for multi-objective bayesian optimization D Hernández-Lobato, J Hernandez-Lobato, A Shah, R Adams International Conference on Machine Learning, 1492-1501, 2016	55	2016
Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control N Jaques, S Gu, D Bahdanau, JM Hernández-Lobato, RE Turner, D Eck Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	49	2017
Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space JM Hernández-Lobato, J Requeima, EO Pyzer-Knapp, A Aspuru-Guzik Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	48	2017
Cold-start active learning with robust ordinal matrix factorization N Houlsby, JM Hernández-Lobato, Z Ghahramani International Conference on Machine Learning, 766-774, 2014	46	2014
A general framework for constrained Bayesian optimization using information-based search JM Hernández-Lobato, MA Gelbart, RP Adams, MW Hoffman, ... The Journal of Machine Learning Research 17 (1), 5549-5601, 2016	42	2016
Robust multi-class Gaussian process classification D Hernández-Lobato, JM Hernández-Lobato, P Dupont Advances in neural information processing systems, 280-288, 2011	42	2011

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