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Manifesto

Dettaglio Insegnamento

Contesto
Anno Accademico 2021/2022
Corso di Studi Dott. - MI (1385) Modelli e Metodi Matematici per l'Ingegneria / Mathematical Models and Methods in Engineering
Anno di Corso 1

Scheda Insegnamento
Codice Identificativo 056320
Denominazione Insegnamento MATHEMATICAL METHODS FOR DEEP LEARNING
Tipo Insegnamento MONODISCIPLINARE
Crediti Formativi Universitari (CFU) 5.0
Programma sintetico The course is split into 4 parts: (a) Introduction to Deep Learning (4h) (b) Approximation Theory and Neural Networks (NN) (6h): old and recent results on the approximation power of NN will be discussed with a particular emphasis on the role of the depth of the NN. (c) Optimization and Deep Neural Networks (10h): Optimization algorithms to train DNN will be presented and discussed with a particular emphasis on nonconvex optimization, recent results dealing with convergence of the learning process and techniques of automatic differentiation. (d) Deep Learning and Partial Differential Equations (6h): the possibility of employing DL in the context of the numerical solution of PDEs will be explored.
Settori Scientifico Disciplinari (SSD)
Codice SSD Descrizione SSD CFU
MAT/08 ANALISI NUMERICA 5.0

Dettaglio
Scaglione Docente Programma dettagliato
Da (compreso) A (escluso)
A ZZZZ Verani Marco, Miglio Edie
manifestidott v. 1.7.0 / 1.7.0
Area Servizi ICT
12/08/2022