- Sprache
-
Englisch
- Umfang
-
Online-Ressource
- Anmerkungen
-
München, Ludwig-Maximilians-Universität, Dissertation, 2022
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Schlagwort
-
Neuronales Netz
Inverses Problem
Maschinelles Lernen
Deep learning
Bildverarbeitung
Adaptive Optik
- Urheber
-
Andrade Loarca, Héctor
- Beteiligte Personen und Organisationen
-
Kutyniok, Gitta
- Ereignis
-
Veröffentlichung
- (wo)
-
München
- (wer)
-
Universitätsbibliothek der Ludwig-Maximilians-Universität
- (wann)
-
2022
- DOI
-
10.5282/edoc.30596
- URN
-
urn:nbn:de:bvb:19-305969
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
24.05.2025, 14:51 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Andrade Loarca, Héctor
- Kutyniok, Gitta
- Universitätsbibliothek der Ludwig-Maximilians-Universität
Entstanden
- 2022
Ähnliche Objekte (12)
DeepBase: Deep Inspection of Neural Networks
Training deep quantum neural networks
Operator compression with deep neural networks
Deep neural networks and PIDE discretizations
Towards automatically-tuned deep neural networks
Optimization landscape of deep neural networks
Deep Neural Networks motivated by PDEs
Assessing the reliability of deep neural networks
Automatic drum transcription with deep neural networks
Understanding memory representations through deep neural networks
Formal Analysis of Deep Binarized Neural Networks
Harmonic analysis of deep convolutional neural networks
DeepBase: Deep Inspection of Neural Networks
Training deep quantum neural networks
Operator compression with deep neural networks
Deep neural networks and PIDE discretizations
Towards automatically-tuned deep neural networks
Optimization landscape of deep neural networks
Deep Neural Networks motivated by PDEs
Assessing the reliability of deep neural networks
Automatic drum transcription with deep neural networks
Understanding memory representations through deep neural networks
Formal Analysis of Deep Binarized Neural Networks
Harmonic analysis of deep convolutional neural networks
DeepBase: Deep Inspection of Neural Networks
Training deep quantum neural networks
Operator compression with deep neural networks
Deep neural networks and PIDE discretizations
Towards automatically-tuned deep neural networks
Optimization landscape of deep neural networks
Deep Neural Networks motivated by PDEs
Assessing the reliability of deep neural networks
Automatic drum transcription with deep neural networks
Understanding memory representations through deep neural networks
Formal Analysis of Deep Binarized Neural Networks