Augmenting Recurrent Neural Networks Resilience by Dropout-Reference-Cited by-同舟云学术

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Augmenting Recurrent Neural Networks Resilience by Dropout

Published:2020-01 Issue:1 Volume:31 Page:345-351
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Bacciu Davide^ORCID,Crecchi Francesco

Funder

Italian Ministry of Education, University, and Research through Project SIR 2014 LIST-IT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/8949827/08668686.pdf?arnumber=8668686

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