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Networks and machine learning to detect Value Added Tax fraud

Aug 22, 2023·
Angelos Alexopoulos
Angelos Alexopoulos
,
Petros Dellaportas
,
Stanley Gyoshev
,
Christos Kotsogiannis
,
Sofia C. Olhede
,
Trifon Pavkov
· 0 min read
PDF
Type
Preprint
Last updated on Aug 22, 2023
Source Themes
Angelos Alexopoulos
Authors
Angelos Alexopoulos
Assistant Professor
← A machine learning approach to construct quarterly data on intangible investment for Eurozone Sep 1, 2023
Variance reduction for Metropolis-Hastings samplers Apr 1, 2023 →

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