10.1k citations · 10.9k across the 10 of their papers we have counts for
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cs.LG2022★ 4 cited
Hyperbolic Deep Reinforcement Learning
Edoardo Cetin, Benjamin Chamberlain, Michael Bronstein +1
We propose a new class of deep reinforcement learning (RL) algorithms that model latent representations in hyperbolic space. Sequential decision-making requires reasoning about the…
cs.LG2022★ 35 cited
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou
Offline reinforcement learning (RL), which aims to learn an optimal policy using a previously collected static dataset, is an important paradigm of RL. Standard RL methods often pe…