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Displaying 31 - 38 of 38
Measure-Valued Derivatives for Reinforcement Learning
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
IngenieurwissenschaftenInformatik
Optical Absorption Studies and Quantum Chemistry of a Tin Nanoparticle
Semiconductors are the fundament of modern technology and still in the focus of current research. With decreasing size ...
NaturwissenschaftenPhysikalische und Theoretische Chemie
When to Trust Your Model in Model-based Value Expansion?
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
IngenieurwissenschaftenInformatik
Balloon Estimators for Improving and Scaling the Nonparametric Off-Policy Policy Gradient
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...
IngenieurwissenschaftenInformatik
Constraint Space Projection Reinforcement Learning
The aim of the project is to develop a new family of optimization algorithms to handle convex constraints and evaluate ...
IngenieurwissenschaftenInformatik-
Evaluating and Improving Recurrent Kalman Networks
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
IngenieurwissenschaftenInformatik 
Global Optimization of Aluminum-doped Tin Clusters
Semiconductors are the fundament of modern technology and as such still a topic of current research. With decrease in ...
NaturwissenschaftenPhysikalische und Theoretische Chemie-
Efficient representations of deep neural networks
Deep neural networks (DNNs) have gained extreme popularity in recent years, advancing state-of-the- art results in ...
IngenieurwissenschaftenInformatik
