José Miguel Hernández-Lobato
University of Cambridge(GB)
Publications by Year
Research Areas
Gaussian Processes and Bayesian Inference, Machine Learning in Materials Science, Machine Learning and Algorithms, Machine Learning and Data Classification, Generative Adversarial Networks and Image Synthesis
Most-Cited Works
- → Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.(2018)1,970 cited
- → Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks(2015)561 cited
- → Minerva(2016)468 cited
- → Predictive Entropy Search for Efficient Global Optimization of Black-box Functions(2014)396 cited
- → Constrained Bayesian optimization for automatic chemical design using variational autoencoders(2019)355 cited
- → Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators(2016)238 cited
- → GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution(2016)207 cited
- → Predictive Entropy Search for Multi-objective Bayesian Optimization(2015)140 cited
- → Deep Gaussian Processes for Regression using Approximate Expectation Propagation(2016)135 cited