Gaussian process hydrodynamics

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 1 online resource.

Language: Englisch

Bibliographic citation: Gaussian process hydrodynamics ; volume:44 ; number:7 ; day:18 ; month:4 ; year:2023 ; pages:1175-1198 ; date:7.2023
Applied mathematics and mechanics ; 44, Heft 7 (18.4.2023), 1175-1198, 7.2023

Creator: Owhadi, H.

Contributor: SpringerLink (Online service)

DOI: 10.1007/s10483-023-2990-9

URN: urn:nbn:de:101:1-2023093011035882418937

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

Last update: 14.08.2025, 10:50 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

Owhadi, H.
SpringerLink (Online service)

Other Objects (12)

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

Hochschulschrift

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

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.

Gaussian process hydrodynamics

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

Diabatization via Gaussian Process Regression

Variational Tobit Gaussian Process Regression

Revisiting statefinder via Gaussian process

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

Scalable Inference in Latent Gaussian Process Models

Quantum Gaussian process regression for Bayesian optimization

Adversarial vulnerability bounds for Gaussian process classification

Gaussian process kernels for partial physical insight

A robust approach to Gaussian process implementation

Related objects

Reset password