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Found 3 papers, 3 papers with code
MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning
Meta-reinforcement learning (meta-RL) is a promising framework for tackling challenging domains requiring efficient exploration.
NeRN -- Learning Neural Representations for Neural Networks
Neural Representations have recently been shown to effectively reconstruct a wide range of signals from 3D meshes and shapes to images and videos.
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach
We show that our approach leads to bounds that depend on the dimension of the task distribution.
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