Open AccessFully Spiking Variational Autoencoder
Author(s) -
Hiromichi Kamata,
Yusuke Mukuta,
Tatsuya Harada
Publication year - 2022
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.v36i6.20665
Subject(s) - autoencoder , computer science , spiking neural network , artificial intelligence , autoregressive model , bernoulli process , latent variable , stability (learning theory) , pattern recognition (psychology) , event (particle physics) , binary number , artificial neural network , algorithm , machine learning , bernoulli's principle , mathematics , statistics , physics , arithmetic , quantum mechanics , engineering , aerospace engineering
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