print

Robust training of vector quantized bottleneck models

author
Lancucki, Adrian
Chorowski, Jan
Sanchez, Guillaume
Marxer, Ricard
Chen, Nanxin
Dolfing, Hans J.G.A.
Khurana, Sameer
Alumäe, Tanel
Laurent, Antoine
statement of authorship
Adrian Łańcucki, Jan Chorowski, Guillaume Sanchez, Ricard Marxer, NanxinChen, Hans Dolfing, Sameer Khurana, Tanel Alumäe, Antoine Laurent
source
2020 International Joint Conference onNeural Networks (IJCNN), 19-24 July 2020, Glasgow, UK : proceedings
location of publication
Danvers
publisher
IEEE
year of publication
2020
pages
art. 163566 : 7 p
conference name, date
2020 International Joint Conference on Neural Networks : IJCNN 2020, Virtual, Glasgow, 19-24 July 2020
conference location
Glasgow, Scotland, United Kingdom
url
https://doi.org/10.1109/IJCNN48605.2020.9207145
subject term
kodeerimine
andmekaitse
mudelipõhine tarkvaraarendus
Scopus
Conference Proceedings at Scopus
Article at Scopus
WOS
Article at WOS
kvartiil
Q2
category (general)
Computer science
category (sub)
Computer science. Artificial intelligence
Computer science. Software
keyword
VQ-VAE (Variational Auto-Encoder)
k-means
discrete information bottle-neck
ISBN
978-1-7281-6926-2
notes
Bibliogr.: 38 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
tarkvarateaduse instituut
language
inglise
Uurimisrühm
Laboratory of language technology
Łańcucki, A., Chorowski, J., Sanchez, G., Marxer, R., Alumäe, T. et al. Robust training of vector quantized bottleneck models // 2020 International Joint Conference onNeural Networks (IJCNN), 19-24 July 2020, Glasgow, UK : proceedings. Danvers : IEEE, 2020. art. 163566 : 7 p. https://doi.org/10.1109/IJCNN48605.2020.9207145