Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Idan Rejwan"'
Publikováno v:
BMC Public Health, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, an
Externí odkaz:
https://doaj.org/article/e86e060daf734edf9df44b3761b6035d
Autor:
Noam Koenigstein, Jonathan Weill, Ori Katz, Itzik Malkiel, Idan Rejwan, Avi Caciularu, Oren Barkan
Publikováno v:
CIKM
We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6ad07e3e83174dd148cfa6f08f039bf
Publikováno v:
BMC Public Health
BMC Public Health, Vol 21, Iss 1, Pp 1-13 (2021)
BMC Public Health, Vol 21, Iss 1, Pp 1-13 (2021)
Background Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop
Publikováno v:
ACL
This paper presents the Bayesian Hierarchical Words Representation (BHWR) learning algorithm. BHWR facilitates Variational Bayes word representation learning combined with semantic taxonomy modeling via hierarchical priors. By propagating relevant in