Learning high-dimensional surrogates from mantle convection simulations

Agarwal, Siddhant and Tosi, Nicola and Kessel, Pan and Breuer, Doris and Padovan, Sebastiano and Montavon, Grégoire (2020) Learning high-dimensional surrogates from mantle convection simulations. APS Division of Fluid Dynamics 2020, Virtual conference.

Full text not available from this repository.

Item URL in elib:

https://elib.dlr.de/138594/

Document Type:

Conference or Workshop Item (Lecture)

Title:

Learning high-dimensional surrogates from mantle convection simulations

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD
Agarwal, Siddhant	Siddhant.Agarwal (at) dlr.de	https://orcid.org/0000-0002-0840-2114
Tosi, Nicola	nicola.tosi (at) dlr.de	https://orcid.org/0000-0002-4912-2848
Kessel, Pan	pan.kessel (at) campus.tu-berlin.de	UNSPECIFIED
Breuer, Doris	Doris.Breuer (at) dlr.de	https://orcid.org/0000-0001-9019-5304
Padovan, Sebastiano	Sebastiano.Padovan (at) dlr.de	https://orcid.org/0000-0002-8652-3704
Montavon, Grégoire	Institut für Softwaretechnik und Theoretische Informatik, Technische Universität Berlin	UNSPECIFIED

Date:

2020

Refereed publication:

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Mars; thermal evolution; machine learning

Event Title:

APS Division of Fluid Dynamics 2020

Event Location:

Virtual conference

Event Type:

international Conference

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Space Exploration

DLR - Research area:

Raumfahrt

DLR - Program:

R EW - Space Exploration

DLR - Research theme (Project):

R - Exploration of the Solar System

Location:

Berlin-Adlershof

Institutes and Institutions:

Institute of Planetary Research > Planetary Physics

Deposited By:

Tosi, Nicola

Deposited On:

30 Nov 2020 13:54

Last Modified:

30 Nov 2020 13:54

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