Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Slimane, Arselane Hadj"'
Neural ordinary differential equations (neural ODEs) have emerged as a natural tool for supervised learning from a control perspective, yet a complete understanding of their optimal architecture remains elusive. In this work, we examine the interplay
Externí odkaz:
http://arxiv.org/abs/2401.09902
Autor:
Álvarez-López A; Universidad Autónoma de Madrid, Departamento de Matemáticas, C. Francisco Tomás y Valiente, 7, Madrid, 28049, Spain; Friedrich-Alexander-Universität Erlangen-Nürnberg, Department of Mathematics, Chair for Dynamics, Control, Machine Learning, and Numerics (Alexander von Humboldt Professorship), Cauerstraße, 11, Erlangen, 91058, Germany. Electronic address: antonio.alvarezl@uam.es., Slimane AH; ENS Paris Saclay, Avenue des sciences, 4, Gif-sur-Yvette, 91190, France. Electronic address: arselane.hadj_slimane@ens-paris-saclay.fr., Zuazua E; Universidad Autónoma de Madrid, Departamento de Matemáticas, C. Francisco Tomás y Valiente, 7, Madrid, 28049, Spain; Friedrich-Alexander-Universität Erlangen-Nürnberg, Department of Mathematics, Chair for Dynamics, Control, Machine Learning, and Numerics (Alexander von Humboldt Professorship), Cauerstraße, 11, Erlangen, 91058, Germany; Fundación Deusto, Av. de las Universidades, 24, Bilbao, 48007, Spain. Electronic address: enrique.zuazua@fau.de.
Publikováno v:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2024 Dec; Vol. 180, pp. 106640. Date of Electronic Publication: 2024 Aug 19.
