Deeply Tough Framework, Grammar for Agents, and Too Much Screen Time?
Journal Club
English - May 26, 2020 21:24 - 34 minutes - 39.4 MBMathematics Science Education computerscience machinelearning modelinterpretability Homepage Download Google Podcasts Overcast Castro Pocket Casts RSS feed
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Today on the show Kyle discusses research which suggests that time on screens has little impact on kids' social skills. Lan talks about DeeplyTough a deep learning framework targeting the protein pocket matching problem - try to answer whether a pair of protein pockets can bind to the same ligand.George's paper this week is about defining a grammar for interpretable agents. By basing this formalism on a corpus of human explanation dialogues the authors hope to produce a more "grounded" protocol.