- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Berlin, ESMT Berlin, Dissertation, 2021
- Schlagwort
-
Leadership
Learning
- Ereignis
-
Veröffentlichung
- (wo)
-
Berlin
- (wer)
-
ESMT European School of Management and Technology
- (wann)
-
2022
- Urheber
-
Marquart, Ingo
- Beteiligte Personen und Organisationen
- URN
-
urn:nbn:de:101:1-2022070108271044568918
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 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
- Marquart, Ingo
- Bothner, Matthew S.
- Piezunka, Henning
- European School of Management and Technology
- ESMT European School of Management and Technology
Entstanden
- 2022
Ähnliche Objekte (12)
Geometric deep learning and equivariant neural networks
Variational tensor neural networks for deep learning
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Learning deep networks with crowdsourcing for relevance evaluation
Biosignals learning and synthesis using deep neural networks
Computational Protein Design with Deep Learning Neural Networks
Theory of Deep Convolutional Neural Networks and Distributed Learning
Convergence of gradient flows for learning deep linear networks
Learning cartographic building generalization with deep convolutional neural networks
Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra
Learning representations of atomistic systems with deep neural networks
Learning adaptive receptive fields for deep image parsing networks
Geometric deep learning and equivariant neural networks
Variational tensor neural networks for deep learning
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Learning deep networks with crowdsourcing for relevance evaluation
Biosignals learning and synthesis using deep neural networks
Computational Protein Design with Deep Learning Neural Networks
Theory of Deep Convolutional Neural Networks and Distributed Learning
Convergence of gradient flows for learning deep linear networks
Learning cartographic building generalization with deep convolutional neural networks
Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra
Learning representations of atomistic systems with deep neural networks
Learning adaptive receptive fields for deep image parsing networks
Geometric deep learning and equivariant neural networks
Variational tensor neural networks for deep learning
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Learning deep networks with crowdsourcing for relevance evaluation
Biosignals learning and synthesis using deep neural networks
Computational Protein Design with Deep Learning Neural Networks
Theory of Deep Convolutional Neural Networks and Distributed Learning
Convergence of gradient flows for learning deep linear networks
Learning cartographic building generalization with deep convolutional neural networks
Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra
Learning representations of atomistic systems with deep neural networks