Estimation and visualization of process states using latent variable models based on Gaussian process

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Estimation and visualization of process states using latent variable models based on Gaussian process ; year:2021
Analytical science advances ; (2021)

Creator: Kaneko, Hiromasa

DOI: 10.1002/ansa.202000122

URN: urn:nbn:de:101:1-2021020411504840220772

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

Last update: 15.08.2025, 7:35 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

Kaneko, Hiromasa

Other Objects (12)

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Arbeitspapier

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Arbeitspapier

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Arbeitspapier

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

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.

Estimation and visualization of process states using latent variable models based on Gaussian process

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

Scalable Inference in Latent Gaussian Process Models

Gaussian process hydrodynamics

Gaussian Process models and global optimization with categorical variables

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

Visualization of Business Process Models

Gaussian Process Forecast with multidimensional distributional entries

Gaussian-process-based robot learning from demonstration

Variational inference for composite Gaussian process models

Fast deep mixtures of Gaussian process experts

Quantum Gaussian process regression for Bayesian optimization

Related objects

Reset password