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Reinforcement Learning with Augmented Data


Aravind Srinivas: New paper - Reinforcement Learning with Augmented Data (RAD)! Data augmentation *alone* can achieve SoTA on DMControl and test-time generalization on ProcGen! Paper: Project Page: Code:

6 replies, 522 likes

Michael (Misha) Laskin: New updates to RAD (RL + data augs) answer the following: 1)Why does random crop work so well? -> translation invariance 2)Does data aug work for state-based RL too? -> yes SOTA on DeepMind control (pixel-based RL) and OpenAI gym (state-based RL). 1/N

4 replies, 136 likes

Ekin Dogus Cubuk: Cool work that shows image augmentations can help RL generalization significantly. Also interesting to see 'crop' was the most effective operation in RL — I would say this is the case for vision tasks (both training and test time) too.

0 replies, 31 likes

Markus Wulfmeier 🏡: 'Nothing is as powerful as an idea whose time has come!' Image augmentations are enabling some considerable performance boost in Deep RL #ReinforcementLearning

1 replies, 15 likes

Popular ML resources: The most popular ArXiv tweet in the last 24h:

0 replies, 3 likes

roadrunner01: Reinforcement Learning with Augmented Data pdf: abs: github: project page:

0 replies, 3 likes

Animesh Garg: Key Idea: Inferring local causal models (LCMs) from a global causal model given an object-oriented state representation. LCMs can generate counterfactual experiences that are causally valid in the global model. HER ( and RAD (

1 replies, 3 likes

HotComputerScience: Most popular computer science paper of the day: "Reinforcement Learning with Augmented Data"

0 replies, 1 likes


Found on May 01 2020 at

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