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CURL: Contrastive Unsupervised Representations for Reinforcement Learning

Machine Learning Street Talk (MLST)

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The Power of Pixel Inputs in Robotic Control

This chapter explores the advantages of utilizing pixel inputs for controlling robotic agents, highlighting its potential to streamline model training across different robots and tasks. It also examines the difficulties in predicting state variables from pixel data and the ability of neural networks to surpass traditional methods in specific environments.

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