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Unravelling interior evolution of terrestrial planets using machine learning.

Agarwal, Siddhant and Tosi, Nicola and Breuer, Doris and Kessel, Pan and Montavon, Grégoire (2019) Unravelling interior evolution of terrestrial planets using machine learning. Artificial Intelligence in Astronom, 2019, Munich, Germany.

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Official URL: https://www.eso.org/sci/meetings/2019/AIA2019/PDF/Contributed/Agarwal.pdf


Item URL in elib:https://elib.dlr.de/136680/
Document Type:Conference or Workshop Item (Speech)
Title:Unravelling interior evolution of terrestrial planets using machine learning.
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Agarwal, SiddhantSiddhant.Agarwal (at) dlr.dehttps://orcid.org/0000-0002-0840-2114
Tosi, Nicolanicola.tosi (at) dlr.dehttps://orcid.org/0000-0002-4912-2848
Breuer, DorisDoris.Breuer (at) dlr.dehttps://orcid.org/0000-0001-9019-5304
Kessel, Panpan.kessel (at) campus.tu-berlin.deUNSPECIFIED
Montavon, Grégoiregregoire.montavon (at) tu-berlin.deUNSPECIFIED
Date:July 2019
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Inverse problem, Mixture Density Networks, Thermal Evolution, Mars, Mantle Convection
Event Title:Artificial Intelligence in Astronom
Event Location:Munich, Germany
Event Type:international Conference
Event Dates:2019
Organizer:European Southern Observatory
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Science and Exploration
DLR - Research area:Raumfahrt
DLR - Program:R EW - Erforschung des Weltraums
DLR - Research theme (Project):R - Vorhaben Exploration des Sonnensystems
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Planetary Research
Institute of Planetary Research > Planetary Physics
Deposited By: Agarwal, Siddhant
Deposited On:16 Oct 2020 08:18
Last Modified:16 Oct 2020 08:18

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