- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1573-0565
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
A topological insight into restricted Boltzmann machines ; day:15 ; month:7 ; year:2016 ; pages:1-28
Machine learning ; (15.7.2016), 1-28
- Creator
-
Mocanu, Decebal Constantin
- Contributor
-
Mocanu, Elena
Nguyen, Phuong H.
Gibescu, Madeleine
Liotta, Antonio
SpringerLink (Online service)
- DOI
-
10.1007/s10994-016-5570-z
- URN
-
urn:nbn:de:1111-20160720872
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:53 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
- Mocanu, Decebal Constantin
- Mocanu, Elena
- Nguyen, Phuong H.
- Gibescu, Madeleine
- Liotta, Antonio
- SpringerLink (Online service)
Other Objects (12)
Learning Informative Features from Restricted Boltzmann Machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Anomaly detection speed-up by quantum restricted Boltzmann machines
Gaussian-binary restricted Boltzmann machines for modeling natural image statistics
Multilayer perceptrons, Hopfield’s associative memories, and restricted Boltzmann machines
Learning natural image statistics with variants of restricted Boltzmann machines
Using Memristors for Robust Local Learning of Hardware Restricted Boltzmann Machines
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines
Three learning stages and accuracy–efficiency tradeoff of restricted Boltzmann machines
Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling
Accuracy of restricted Boltzmann machines for the one-dimensional J1−J2 Heisenberg model
Learning Informative Features from Restricted Boltzmann Machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Anomaly detection speed-up by quantum restricted Boltzmann machines
Gaussian-binary restricted Boltzmann machines for modeling natural image statistics
Multilayer perceptrons, Hopfield’s associative memories, and restricted Boltzmann machines
Learning natural image statistics with variants of restricted Boltzmann machines
Using Memristors for Robust Local Learning of Hardware Restricted Boltzmann Machines
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines
Three learning stages and accuracy–efficiency tradeoff of restricted Boltzmann machines
Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling
Accuracy of restricted Boltzmann machines for the one-dimensional J1−J2 Heisenberg model
Learning Informative Features from Restricted Boltzmann Machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Analyzing joint brand purchases by conditional restricted Boltzmann machines
Anomaly detection speed-up by quantum restricted Boltzmann machines
Gaussian-binary restricted Boltzmann machines for modeling natural image statistics
Multilayer perceptrons, Hopfield’s associative memories, and restricted Boltzmann machines
Learning natural image statistics with variants of restricted Boltzmann machines
Using Memristors for Robust Local Learning of Hardware Restricted Boltzmann Machines
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines
Three learning stages and accuracy–efficiency tradeoff of restricted Boltzmann machines
Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling