Sound-based sleep assessment with controllable subject-dependent embedding using Variational Domain Adversarial Neural Network

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 1 online resource.

Language: Englisch

Bibliographic citation: Sound-based sleep assessment with controllable subject-dependent embedding using Variational Domain Adversarial Neural Network ; day:4 ; month:7 ; year:2023 ; pages:1-11
International journal of data science and analytics ; (4.7.2023), 1-11

Creator: Fukui, Ken-ichi
Ishimaru, Shunya
Kato, Takafumi
Numao, Masayuki

Contributor: SpringerLink (Online service)

DOI: 10.1007/s41060-023-00407-7

URN: urn:nbn:de:101:1-2023093011265394415946

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:56 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Fukui, Ken-ichi
Ishimaru, Shunya
Kato, Takafumi
Numao, Masayuki
SpringerLink (Online service)

Other Objects (12)

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Sound-based sleep assessment with controllable subject-dependent embedding using Variational Domain Adversarial Neural Network

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Variational inference based adversarial domain adaptation

Adversarial and variational autoencoders improve metagenomic binning

Adversarial attacks on graph-level embedding methods: a case study

Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach

Unsupervised Learning of Network Embedding with Variational Autoencoder Framework

Variational Autoencoders and Generative Adversarial Networks for Multivariate Scenario Generation

Controllable text-to-speech system : speaking style control using hierarchical variational autoencoder

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

DLP 4D‐Printing of Remotely, Modularly, and Selectively Controllable Shape Memory Polymer Nanocomposites Embedding Carbon Nanotubes

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means

Related objects

Reset password