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Data curation is crucial for post-training recipes. But how do we curate? Curation is usually manual & tedious. And, it's hard to tell if a strategy in the data will be reliable! We introduce an automatic way to curate, informed by the robot's policy learning.

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Chelsea Finn

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19,910 görüntüleme • 1 yıl önce •via X (Twitter)

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Chelsea Finn profil fotoğrafı
Chelsea Finn1 yıl önce

Key idea: When training on all data, policy success is indicative of whether the strategy it took is good! Paper: Led by @_anniechen_ and @AlecLessing, with @liu_yuejiang @StanfordAILab

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Lucid Scientific, Inc.1 yıl önce

Expand the possibilities of your metabolic research. Resipher tracks real-time cellular oxygen consumption in standard 96-well plates, delivering continuous real-time data directly from your incubator. Request a free virtual demo or quote today >>

Ada Wan profil fotoğrafı
Ada Wan1 yıl önce

No data "cleaning"!!! That's the point. Make it work WITHOUT hacking through data / "data curation". If an algorithm works with any data, without any "data cleaning/curation", that indicates there is some good generalization power in the algo. If the algo only works (well) 1/

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