4 citations · 4 across the 2 of their papers we have counts for
3 papers · 1 filter
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
Jens Petersen, Gregor Köhler, David Zimmerer +3
Neural Processes (NPs) are a family of conditional generative models that are able to model a distribution over functions, in a way that allows them to perform predictions at test…
Sample-Efficient Automated Deep Reinforcement Learning
Jörg K. H. Franke, Gregor Köhler, André Biedenkapp +1
Despite significant progress in challenging problems across various domains, applying state-of-the-art deep reinforcement learning (RL) algorithms remains challenging due to their…
Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control
Jörg K. H. Franke, Gregor Köhler, Noor Awad +1
Current Deep Reinforcement Learning algorithms still heavily rely on handcrafted neural network architectures. We propose a novel approach to automatically find strong topologies f…