José Miguel Hernández-Lobato

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Daniel Hernández-LobatoLecturer of Computer Science, Universidad Autónoma de MadridAdresse e-mail validée de uam.es
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Ryan P. AdamsPrinceton UniversityAdresse e-mail validée de princeton.edu
Richard E TurnerProfessor, University of CambridgeAdresse e-mail validée de cam.ac.uk
Yingzhen LiImperial College LondonAdresse e-mail validée de imperial.ac.uk
Cheng ZhangPrincipal Researcher, Microsoft Research, Cambridge, UKAdresse e-mail validée de kth.se
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Adresse e-mail validée de utoronto.ca
Matt J. KusnerAssociate Professor, University College LondonAdresse e-mail validée de ucl.ac.uk
Brooks PaigeAssociate Professor, University College LondonAdresse e-mail validée de ucl.ac.uk
Chao MaMachine Learning Group, Computational and Biological Learning Lab, University of CambridgeAdresse e-mail validée de cam.ac.uk
Neil HoulsbyGoogleAdresse e-mail validée de google.com
David BrooksHaley Family Professor of Computer Science, Harvard UniversityAdresse e-mail validée de eecs.harvard.edu
Gu-Yeon WeiRobert and Suzanne Case Professor of EE and CS, Harvard University and Fellow, Samsung ResearchAdresse e-mail validée de eecs.harvard.edu
Thang D BuiLecturer, University of SydneyAdresse e-mail validée de sydney.edu.au
Alberto SuárezProfessor of Artificial Intelligence, Computer Science Department, Universidad Autónoma de MadridAdresse e-mail validée de uam.es
Javier AntoranUniversity of CambridgeAdresse e-mail validée de cam.ac.uk
Jorge Aguilera-IparraguirreRecursion PharmaceuticalsAdresse e-mail validée de recursionpharma.com
David DuvenaudAssistant Professor, University of TorontoAdresse e-mail validée de cs.toronto.edu
Marton HavasiUniversity of CambridgeAdresse e-mail validée de cam.ac.uk
Stefan DepewegSiemens AGAdresse e-mail validée de uos.de

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José Miguel Hernández-Lobato

Associate Professor in Machine Learning, University of Cambridge

Adresse e-mail validée de cam.ac.uk - Page d'accueil

Bayesian deep learning approximate inference deep generative modeling automatic molecular design reinforcement learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	1850	2018
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	780	2015
Grammar variational autoencoder MJ Kusner, B Paige, JM Hernández-Lobato International conference on machine learning, 1945-1954, 2017	656	2017
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	581	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 27, 2014	545	2014
Gans for sequences of discrete elements with the gumbel-softmax distribution MJ Kusner, JM Hernández-Lobato arXiv preprint arXiv:1611.04051, 2016	270	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	217	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	197	2016
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	181	2018
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	169	2016
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	144	2016
Deterministic variational inference for robust bayesian neural networks A Wu, S Nowozin, E Meeds, RE Turner, JM Hernandez-Lobato, AL Gaunt arXiv preprint arXiv:1810.03958, 2018	132	2018
Probabilistic matrix factorization with non-random missing data JM Hernández-Lobato, N Houlsby, Z Ghahramani International Conference on Machine Learning, 1512-1520, 2014	131	2014
Collaborative gaussian processes for preference learning N Houlsby, F Huszar, Z Ghahramani, J Hernández-lobato Advances in neural information processing systems 25, 2012	128	2012
Constrained Bayesian optimization for automatic chemical design using variational autoencoders RR Griffiths, JM Hernández-Lobato Chemical science 11 (2), 577-586, 2020	124	2020
Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space JM Hernández-Lobato, J Requeima, EO Pyzer-Knapp, A Aspuru-Guzik International conference on machine learning, 1470-1479, 2017	124	2017
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	124	2015
Stochastic expectation propagation Y Li, JM Hernández-Lobato, RE Turner Advances in neural information processing systems 28, 2015	120	2015
A general framework for constrained Bayesian optimization using information-based search JM Hernández-Lobato, MA Gelbart, RP Adams, MW Hoffman, ... MIT Press, 2016	115	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 International Conference on Machine Learning, 1645-1654, 2017	114	2017

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