Estimating Koopman operators with sketching to provably learn large scale dynamical systems

Meanti, Giacomo; Chatalic, Antoine; Kostic, Vladimir R; Novelli, Pietro; Pontil, Massimiliano; Rosasco, Lorenzo

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eNauka > Rezultati > Estimating Koopman operators with sketching to provably learn large scale dynamical systems

Naziv:	Estimating Koopman operators with sketching to provably learn large scale dynamical systems
Autori:	Meanti, Giacomo; Chatalic, Antoine; Kostic, Vladimir R ; Novelli, Pietro; Pontil, Massimiliano; Rosasco, Lorenzo
Godina:	2023
Publikacija:	ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023)
ISSN:	1049-5258 Pretraži identifikator
Tip rezultata:	Konferencijski rad
WoS-ID:	001220818805036
Scopus-ID:	2-s2.0-85191169954
URI:	https://enauka.gov.rs/handle/123456789/939577 https://cris.uns.ac.rs/en/scientific-results/proceedings-publication/47365
Projekat:	European Research Council (ERC) under the European Union [819789] European Research Council [SLING 819789] AFOSR [FA9550-18-1-7009, FA9550-17-1-0390, BAA-AFRL-AFOSR2016-0007] (European Office of Aerospace Research and Development) EU H2020-MSCA-RISE project [NoMADS -DLV-777826] Center for Brains, Minds and Machines (CBMM) - NSF STC [CCF-1231216, PE0000013-FAIR] European Union [951847, 101070617]
Izvor metapodataka:	(Preuzeto iz Nasi u WoS)
M-kategorija:	Mp kategorija će biti prikazana naknadno.

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