research
∙
05/14/2019
Trajectory-Based Off-Policy Deep Reinforcement Learning
Policy gradient methods are powerful reinforcement learning algorithms a...
share
research
∙
04/04/2019
Meta-Learning Acquisition Functions for Bayesian Optimization
Many practical applications of machine learning require data-efficient b...
research
∙
10/29/2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
Gaussian Processes (GPs) are a generic modelling tool for supervised lea...
research
∙
01/31/2018
Probabilistic Recurrent State-Space Models
State-space models (SSMs) are a highly expressive model class for learni...
research
∙
03/08/2017