José Miguel Hernández-Lobato
4 papers in the PaperMetrix corpus
Papers by this author
-
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
2018 · arXiv (Cornell University)
Posterior sampling for reinforcement learning (PSRL) is an effective method for balancing exploration and exploitation in reinforcement learning. Randomised value functions (RVF) can be viewed as a promising approach to scaling PSRL. However, we show …
-
Taking gradients through experiments: LSTMs and memory proximal policy\n optimization for black-box quantum control
2018 · arXiv (Cornell University)
In this work we introduce the application of black-box quantum control as an\ninteresting rein- forcement learning problem to the machine learning community.\nWe analyze the structure of the reinforcement learning problems arising in\nquantum physics and argue …
-
Bayesian Meta‐Learning for Few‐Shot Reaction Outcome Prediction of Asymmetric Hydrogenation of Olefins
2025 · Angewandte Chemie International Edition
Recent years have witnessed the increasing application of machine learning (ML) in chemical reaction development. These ML methods, in general, require huge training set examples. The published literature has large amounts of data, but there …
-
Scalable Gaussian Process Classification via Expectation Propagation
2015 · arXiv (Cornell University)
Variational methods have been recently considered for scaling the training process of Gaussian process classifiers to large datasets. As an alternative, we describe here how to train these classifiers efficiently using expectation propagation. The proposed …