- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1573-0565
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Unsupervised representation learning with Minimax distance measures ; day:28 ; month:7 ; year:2020 ; pages:1-35
Machine learning ; (28.7.2020), 1-35
- Creator
-
Haghir Chehreghani, Morteza
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1007/s10994-020-05886-4
- URN
-
urn:nbn:de:101:1-2020092422410153809584
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
- 14.08.2025, 10:54 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Haghir Chehreghani, Morteza
- SpringerLink (Online service)
Other Objects (12)
Kalman contrastive unsupervised representation learning
On the construction of minimax-distance (sub-)optimal designs
Unsupervised spatially embedded deep representation of spatial transcriptomics
Unsupervised Graph Representation Learning with Inductive Shallow Node Embedding
Deep unsupervised representation learning for abnormal heart sound classification
The Representation of Popper Measures
Minimax
Sequence to Sequence Autoencoders for Unsupervised Representation Learning from Audio
Unsupervised Point Cloud Representation Learning by Clustering and Neural Rendering
A Skorohod Representation Theorem for Uniform Distance
Minimax Grundstücks-GmbH; Minimax AG
Unsupervised classification : similarity measures, classical and metaheuristic approaches, and applications
Kalman contrastive unsupervised representation learning
On the construction of minimax-distance (sub-)optimal designs
Unsupervised spatially embedded deep representation of spatial transcriptomics
Unsupervised Graph Representation Learning with Inductive Shallow Node Embedding
Deep unsupervised representation learning for abnormal heart sound classification
The Representation of Popper Measures
Minimax
Sequence to Sequence Autoencoders for Unsupervised Representation Learning from Audio
Unsupervised Point Cloud Representation Learning by Clustering and Neural Rendering
A Skorohod Representation Theorem for Uniform Distance
Minimax Grundstücks-GmbH; Minimax AG
Unsupervised classification : similarity measures, classical and metaheuristic approaches, and applications
Kalman contrastive unsupervised representation learning
On the construction of minimax-distance (sub-)optimal designs
Unsupervised spatially embedded deep representation of spatial transcriptomics
Unsupervised Graph Representation Learning with Inductive Shallow Node Embedding
Deep unsupervised representation learning for abnormal heart sound classification
The Representation of Popper Measures
Minimax
Sequence to Sequence Autoencoders for Unsupervised Representation Learning from Audio
Unsupervised Point Cloud Representation Learning by Clustering and Neural Rendering
A Skorohod Representation Theorem for Uniform Distance
Minimax Grundstücks-GmbH; Minimax AG