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pro vyhledávání: '"Shanthamallu, Uday Shankar"'
Graph Neural Networks (GNNs), a generalization of neural networks to graph-structured data, are often implemented using message passes between entities of a graph. While GNNs are effective for node classification, link prediction and graph classifica
Externí odkaz:
http://arxiv.org/abs/2009.14455
Machine learning models that can exploit the inherent structure in data have gained prominence. In particular, there is a surge in deep learning solutions for graph-structured data, due to its wide-spread applicability in several fields. Graph attent
Externí odkaz:
http://arxiv.org/abs/1811.00181
Modern data analysis pipelines are becoming increasingly complex due to the presence of multi-view information sources. While graphs are effective in modeling complex relationships, in many scenarios a single graph is rarely sufficient to succinctly
Externí odkaz:
http://arxiv.org/abs/1810.01405
Autor:
Narayanaswamy, Vivek Sivaraman1, Shanthamallu, Uday Shankar2, Dixit, Abhinav1, Rao, Sunil1, Ayyanar, Raja1, Tepedelenlioglu, Cihan1, Spanias, Andreas S.1, Banavar, Mahesh K.3, Katoch, Sameeksha4, Pedersen, Emma4, Spanias, Photini4, Turaga, Pavan4, Khondoker, Farib4
Publikováno v:
Proceedings of the ASEE Annual Conference & Exposition. 2019, p4237-4254. 18p.
Autor:
Shanthamallu, Uday Shankar, Jones, Alexander, Panés, Julián, Márquez, Ana M. Corraliza, Salas, Azucena, Akmaev, Slava, Ghiassian, Susan D.
Publikováno v:
In Gastroenterology 18-21 May 2024 166(5) Supplement:S
Akademický článek
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Publikováno v:
Synthesis Lectures on Signal Processing; 2021, Vol. 12 Issue 3, pvii-106, 110p
Autor:
Dixit, Abhinav, Shanthamallu, Uday Shankar, Spanias, Andreas, Rao, Sunil, Katoch, Sameeksha, Banavar, Mahesh K., Muniraju, Gowtham, Fan, Jie, Spanias, Photini, Strom, Andrew, Pattichis, Constantinos, Song, Huan
Publikováno v:
ASEE Annual Conference and Exposition, Conference Proceedings
125th ASEE Annual Conference and Exposition
125th ASEE Annual Conference and Exposition
Integrating sensing and machine learning is important in elevating precision in several Internet of Things (IoT) and mobile applications. In our Electrical Engineering classes, we have begun developing self-contained modules to train students in this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______4485::9521eb2173dba97ae8e5a1b619758634
http://gnosis.library.ucy.ac.cy/handle/7/62421
http://gnosis.library.ucy.ac.cy/handle/7/62421