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Physics-guided variational graph autoencoder for air quality inference

 
dc.contributor.authorRodrigo, Esther
dc.contributor.authorDeligiannis, Nikolaos
dc.date.accessioned2025-03-04T19:59:28Z
dc.date.available2025-03-04T19:59:28Z
dc.date.issued2024
dc.description.wosFundingTextThis work was supported in part by the Research Foundation -Flanders (FWO) through the Ph.D. Fellowship Strategic Basic Research under Project 1SC4521N, in part by IMEC under the AAA Project AI-based Air Quality Map and Analytics and in part by the Flemish Government, under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" programme.
dc.identifier.doi10.1109/ICASSP48485.2024.10448194
dc.identifier.eisbn979-8-3503-4485-1
dc.identifier.isbn979-8-3503-4486-8
dc.identifier.issn1520-6149
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/45290
dc.publisherIEEE
dc.source.beginpage6940
dc.source.conference49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
dc.source.conferencedate2024-04-14
dc.source.conferencelocationSeoul
dc.source.endpage6944
dc.source.numberofpages5
dc.title

Physics-guided variational graph autoencoder for air quality inference

dc.typeProceedings paper
dspace.entity.typePublication
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