research
∙
08/12/2023
Value-Distributional Model-Based Reinforcement Learning
Quantifying uncertainty about a policy's long-term performance is import...
share
research
∙
07/07/2023
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Bayesian optimization (BO) is a popular method to optimize costly black-...
research
∙
02/24/2023
Model-Based Uncertainty in Value Functions
We consider the problem of quantifying uncertainty over expected cumulat...
research
∙
12/09/2022
Information-Theoretic Safe Exploration with Gaussian Processes
We consider a sequential decision making task where we are not allowed t...
research
∙
11/22/2021
Transfer Learning with Gaussian Processes for Bayesian Optimization
Bayesian optimization is a powerful paradigm to optimize black-box funct...
research
∙
10/15/2021
On-Policy Model Errors in Reinforcement Learning
Model-free reinforcement learning algorithms can compute policy gradient...
research
∙
06/15/2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Model-based reinforcement learning algorithms with probabilistic dynamic...
research
∙
02/19/2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning
Off-policy reinforcement learning algorithms promise to be applicable in...
research
∙
10/30/2019
Safe Exploration for Interactive Machine Learning
In Interactive Machine Learning (IML), we iteratively make decisions and...
research
∙
07/16/2019
Structured Variational Inference in Unstable Gaussian Process State Space Models
Gaussian processes are expressive, non-parametric statistical models tha...
research
∙
01/10/2019
No-regret Bayesian Optimization with Unknown Hyperparameters
Bayesian optimization (BO) based on Gaussian process models is a powerfu...
research
∙
12/18/2018
Information-Directed Exploration for Deep Reinforcement Learning
Efficient exploration remains a major challenge for reinforcement learni...
research
∙
11/13/2018
Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy
The energy output of photovoltaic (PV) power plants depends on the envir...
research
∙
08/02/2018
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems
Learning algorithms have shown considerable prowess in simulation by all...
research
∙
03/22/2018
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning
Learning-based methods have been successful in solving complex control t...
research
∙
02/23/2018
Verifying Controllers Against Adversarial Examples with Bayesian Optimization
Recent successes in reinforcement learning have lead to the development ...
research
∙
05/23/2017
Safe Model-based Reinforcement Learning with Stability Guarantees
Reinforcement learning is a powerful paradigm for learning optimal polic...
research
∙
06/15/2016
