José Miguel Hernández-Lobato

Author

Also Known As

Hern\'andez-Lobato, Jos\'e Miguel, Hernandez-Lobato, Jose Miguel, Hernández-Lobato, JM, Hernández-Lobato, José Miguel, Hernández-Lobato, Jośe Miguel, Herńandez-Lobato, José Miguel, Jose Miguel Hernandez-Lobato, Jose Miguel Hernández-Lobato, José Hernández-Lobato, José Miguel Hernàndez-Lobato

253

Publications

8.4K

Citations

H-Index

143

Concepts

All Affiliations

University of Cambridge Harvard University Press Universidad Autónoma de Madrid Microsoft (United States)Harvard University

About

José Miguel Hernández-Lobato is an author at University of Cambridge specializing in engineering, machine learning, and computer science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	30	68	4.2K
2	Management	12	12	993
3	Business	5	5	104
4	Education	3	3	61
5	Language Studies	1	1	113

José Miguel Hernández-Lobato

Publications

7.7K

Citations

H-Index

Page 1

	Year	Citations
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules. Rafael Gómez‐Bombarelli, Jennifer N. Wei, David Duvenaud, Apollo (University of Cambridge)	2018	2K
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato, Ryan P. Adams arXiv (Cornell University) Artificial IntelligenceHyperparameter EstimationEngineeringMachine LearningData Science	2015	561
Minerva Brandon Reagen, Paul N. Whatmough, Robert Adolf, ACM SIGARCH Computer Architecture News Deep Neural NetworksEngineeringMachine LearningHardware AccelerationHardware Algorithm	2016	468
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani arXiv (Cornell University) Mathematical ProgrammingArtificial IntelligenceEntropy SearchLarge-scale Global OptimizationEngineering	2014	396
Constrained Bayesian optimization for automatic chemical design using variational autoencoders Ryan‐Rhys Griffiths, José Miguel Hernández-Lobato Chemical Science	2019	347
Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators Brandon Reagen, Paul N. Whatmough, Robert Adolf, EngineeringMachine LearningHardware AlgorithmComputer ArchitectureHardware Systems	2016	238
GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution Matt J. Kusner, José Miguel Hernández-Lobato arXiv (Cornell University) Continuous ApproximationEngineeringMachine LearningGenerative Adversarial NetworkDiscrete Elements	2016	207
Predictive Entropy Search for Multi-objective Bayesian Optimization Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah, arXiv (Cornell University) Artificial IntelligenceLarge-scale Global OptimizationPareto SetMachine LearningEngineering	2015	140
Deep Gaussian Processes for Regression using Approximate Expectation Propagation Thang D. Bui, Daniel Hernández-Lobato, Yingzhen Li, arXiv (Cornell University) Bayesian StatisticEngineeringMachine LearningData ScienceGaussian Processes	2016	135
A General Framework for Constrained Bayesian Optimization using Information-based Search José Miguel Hernández-Lobato, Zoubin Ghahramani Apollo (University of Cambridge)	2016	130

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