Open AccessGated Linear Networks
Author(s) -
Joel Veness,
Tor Lattimore,
David Budden,
Avishkar Bhoopchand,
Christopher Mattern,
Agnieszka GrabskaBarwińska,
Eren Sezener,
Jianan Wang,
Péter Tóth,
Simon Schmitt,
Marcus Hütter
Publication year - 2021
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - Uncategorized
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v35i11.17202
Subject(s) - computer science , forgetting , dropout (neural networks) , artificial intelligence , deep learning , artificial neural network , activation function , backpropagation , feature (linguistics) , mechanism (biology) , machine learning , epistemology , linguistics , philosophy
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