José Miguel Hernández-Lobato

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	All	Since 2015
Citations	5201	4999
h-index	30	28
i10-index	65	60

1700

850

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1275

2010201120122013201420152016201720182019202014 15 19 47 71 133 289 515 938 1421 1686

Co-authors

Daniel Hernández-LobatoLecturer of Computer Science, Universidad 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 TurnerProfessor, 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
Matt J. KusnerAssociate Professor, University College LondonVerified email at ucl.ac.uk
Cheng ZhangMicrosoft Research, CambridgeVerified email at kth.se
Brooks PaigeAssociate Professor, University College LondonVerified email at ucl.ac.uk
Neil HoulsbyGoogleVerified email at google.com
David BrooksHaley Family Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Gu-Yeon WeiProfessor of EE and CS, Harvard UniversityVerified email at eecs.harvard.edu
Thang D BuiResearch Scientist, Uber AI; Lecturer, University of SydneyVerified email at sydney.edu.au
Alberto SuárezProfessor of Artificial Intelligence, Computer Science Department, Universidad Autónoma de MadridVerified email at uam.es
Sebastian NowozinPartner Researcher, Microsoft Research (Cambridge, UK)Verified email at microsoft.com
Jorge Aguilera-IparraguirreRecursion PharmaceuticalsVerified email at recursionpharma.com
David DuvenaudAssistant Professor, University of TorontoVerified email at cs.toronto.edu
Matthew W. HoffmanUniversity of CambridgeVerified email at cam.ac.uk
Stefan DepewegSiemens AGVerified email at uos.de
Steffen UdluftLearning Systems, SiemensVerified email at siemens.com

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


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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	972	2018
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International Conference on Machine Learning, 1861-1869, 2015	499	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	398	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	384	2014
Grammar variational autoencoder MJ Kusner, B Paige, JM Hernández-Lobato arXiv preprint arXiv:1703.01925, 2017	321	2017
Gans for sequences of discrete elements with the gumbel-softmax distribution MJ Kusner, JM Hernández-Lobato arXiv preprint arXiv:1611.04051, 2016	179	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	143	2016
Black-box alpha divergence minimization J Hernandez-Lobato, Y Li, M Rowland, T Bui, D Hernández-Lobato, ... International Conference on Machine Learning, 1511-1520, 2016	134	2016
Collaborative Gaussian processes for preference learning N Houlsby, F Huszar, Z Ghahramani, J Hernández-lobato Advances in neural information processing systems 25, 2096-2104, 2012	109	2012
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	106	2016
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	97	2016
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	91	2013
Stochastic expectation propagation Y Li, JM Hernández-Lobato, RE Turner Advances in neural information processing systems, 2323-2331, 2015	89	2015
Probabilistic matrix factorization with non-random missing data JM Hernández-Lobato, N Houlsby, Z Ghahramani International Conference on Machine Learning, 1512-1520, 2014	86	2014
Predictive entropy search for bayesian optimization with unknown constraints JM Hernández-Lobato, M Gelbart, M Hoffman, R Adams, Z Ghahramani International conference on machine learning, 1699-1707, 2015	81	2015
Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space JM Hernández-Lobato, J Requeima, EO Pyzer-Knapp, A Aspuru-Guzik arXiv preprint arXiv:1706.01825, 2017	77	2017
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 International Conference on Machine Learning, 1645-1654, 2017	74	2017
Decomposition of uncertainty in Bayesian deep learning for efficient and risk-sensitive learning S Depeweg, JM Hernandez-Lobato, F Doshi-Velez, S Udluft International Conference on Machine Learning, 1184-1193, 2018	71	2018
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	70	2016
Robust multi-class Gaussian process classification D Hernández-Lobato, J Hernández-lobato, P Dupont Advances in neural information processing systems 24, 280-288, 2011	57	2011

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