José Miguel Hernández-Lobato

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.

Rafael Gómez‐Bombarelli, Jennifer N. Wei, David Duvenaud et al. · Apollo (University of Cambridge) · 2018 · 2K citations · Full text

Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks

José Miguel Hernández-Lobato, Ryan P. Adams · arXiv (Cornell University) · 2015 · 561 citations · Full text

Artificial Intelligence, Hyperparameter Estimation, Engineering +13

Minerva

Brandon Reagen, Paul N. Whatmough, Robert Adolf et al. · ACM SIGARCH Computer Architecture News · 2016 · 468 citations

Deep Neural Networks, Engineering, Machine Learning +13

Predictive Entropy Search for Efficient Global Optimization of Black-box Functions

José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani · arXiv (Cornell University) · 2014 · 396 citations · Full text

Mathematical Programming, Artificial Intelligence, Entropy Search +18

Constrained Bayesian optimization for automatic chemical design using variational autoencoders

Ryan‐Rhys Griffiths, José Miguel Hernández-Lobato · Chemical Science · 2019 · 347 citations · Full text