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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
19042018
Probabilistic backpropagation for scalable learning of bayesian neural networks
JM Hernández-Lobato, R Adams
International conference on machine learning, 1861-1869, 2015
8062015
Grammar variational autoencoder
MJ Kusner, B Paige, JM Hernández-Lobato
International conference on machine learning, 1945-1954, 2017
6742017
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
5882016
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
5552014
Gans for sequences of discrete elements with the gumbel-softmax distribution
MJ Kusner, JM Hernández-Lobato
arXiv preprint arXiv:1611.04051, 2016
2752016
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
2182016
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
2022016
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
1912018
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
1732016
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
1442016
Probabilistic matrix factorization with non-random missing data
JM Hernández-Lobato, N Houlsby, Z Ghahramani
International Conference on Machine Learning, 1512-1520, 2014
1372014
Constrained Bayesian optimization for automatic chemical design using variational autoencoders
RR Griffiths, JM Hernández-Lobato
Chemical science 11 (2), 577-586, 2020
1362020
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
1352018
Collaborative gaussian processes for preference learning
N Houlsby, F Huszar, Z Ghahramani, J Hernández-lobato
Advances in neural information processing systems 25, 2012
1302012
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
1262017
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
1262015
Stochastic expectation propagation
Y Li, JM Hernández-Lobato, RE Turner
Advances in neural information processing systems 28, 2015
1252015
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
1172017
A general framework for constrained Bayesian optimization using information-based search
JM Hernández-Lobato, MA Gelbart, RP Adams, MW Hoffman, ...
MIT Press, 2016
1172016
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