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José Miguel Hernández-Lobato
José Miguel Hernández-Lobato
Associate Professor in Machine Learning, University of Cambridge
Verified email at cam.ac.uk - Homepage
Title
Cited by
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
20862018
Probabilistic backpropagation for scalable learning of bayesian neural networks
JM Hernández-Lobato, R Adams
International conference on machine learning, 1861-1869, 2015
8582015
Grammar variational autoencoder
MJ Kusner, B Paige, JM Hernández-Lobato
International conference on machine learning, 1945-1954, 2017
7462017
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
6172016
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
5932014
Gans for sequences of discrete elements with the gumbel-softmax distribution
MJ Kusner, JM Hernández-Lobato
arXiv preprint arXiv:1611.04051, 2016
2932016
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
2242018
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
2222016
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
2112016
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
1832016
Constrained Bayesian optimization for automatic chemical design using variational autoencoders
RR Griffiths, JM Hernández-Lobato
Chemical science 11 (2), 577-586, 2020
1672020
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
1492016
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
1472018
Probabilistic matrix factorization with non-random missing data
JM Hernández-Lobato, N Houlsby, Z Ghahramani
International Conference on Machine Learning, 1512-1520, 2014
1462014
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
1362017
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
1352015
Collaborative gaussian processes for preference learning
N Houlsby, F Huszar, Z Ghahramani, J Hernández-lobato
Advances in neural information processing systems 25, 2012
1332012
Stochastic expectation propagation
Y Li, JM Hernández-Lobato, RE Turner
Advances in neural information processing systems 28, 2015
1282015
A general framework for constrained Bayesian optimization using information-based search
JM Hernández-Lobato, MA Gelbart, RP Adams, MW Hoffman, ...
MIT Press, 2016
1272016
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
1242017
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