- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: https://doi.org/10.48550/arXiv.1912.04132
In: https://doi.org/10.1109/IJCNN48605.2020.9206768
In: https://doi.org/10.1007/978-3-031-31836-8_4
In: https://doi.org/10.1609/aaai.v37i11.26496
In: https://doi.org/10.48550/arXiv.2211.00384
Bonn, Rheinische Friedrich-Wilhelms-Universität, Dissertation, 2024
- Schlagwort
-
Neuronales Netz
Maschinelles Lernen
- Ereignis
-
Veröffentlichung
- (wo)
-
Bonn
- (wer)
-
Universitäts- und Landesbibliothek Bonn
- (wann)
-
2024
- Urheber
-
Cvejoski, Kostadin
- Beteiligte Personen und Organisationen
-
Bauckhage, Christian
Wrobel, Stefan
- Handle
-
20.500.11811/11435
- URN
-
urn:nbn:de:hbz:5-74907
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 14.08.2025, 11:04 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
- Cvejoski, Kostadin
- Bauckhage, Christian
- Wrobel, Stefan
- Universitäts- und Landesbibliothek Bonn
Entstanden
- 2024
Ähnliche Objekte (12)
Dynamic language models for hybrid speech recognition
Individualizing deep dynamic models for psychological resilience data
Dynamic approaches to natural language
Trusting deep learning natural-language models via local and global explanations
ProtGPT2 is a deep unsupervised language model for protein design
Composition Based Oxidation State Prediction of Materials Using Deep Learning Language Models
Integration of pre-trained protein language models into geometric deep learning networks
Integrated image-based deep learning and language models for primary diabetes care
A systematic review of deep learning chemical language models in recent era
Four Essays on Language Competition and Dynamic Language Policy Evaluation
Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models
dACL: the deep constraint and action language for static and dynamic semantic definition in Melanee
Dynamic language models for hybrid speech recognition
Individualizing deep dynamic models for psychological resilience data
Dynamic approaches to natural language
Trusting deep learning natural-language models via local and global explanations
ProtGPT2 is a deep unsupervised language model for protein design
Composition Based Oxidation State Prediction of Materials Using Deep Learning Language Models
Integration of pre-trained protein language models into geometric deep learning networks
Integrated image-based deep learning and language models for primary diabetes care
A systematic review of deep learning chemical language models in recent era
Four Essays on Language Competition and Dynamic Language Policy Evaluation
Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models
dACL: the deep constraint and action language for static and dynamic semantic definition in Melanee
Dynamic language models for hybrid speech recognition
Individualizing deep dynamic models for psychological resilience data
Dynamic approaches to natural language
Trusting deep learning natural-language models via local and global explanations
ProtGPT2 is a deep unsupervised language model for protein design
Composition Based Oxidation State Prediction of Materials Using Deep Learning Language Models
Integration of pre-trained protein language models into geometric deep learning networks
Integrated image-based deep learning and language models for primary diabetes care
A systematic review of deep learning chemical language models in recent era
Four Essays on Language Competition and Dynamic Language Policy Evaluation
Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models