Toward Constraining Mars' Thermal Evolution Using Machine Learning

Toward Constraining Mars' Thermal Evolution Using Machine Learning

Abstract The thermal and convective evolution of terrestrial planets like Mars is governed by a number of initial conditions and parameters, which are poorly constrained. We use Mixture Density Networks (MDN) to invert various sets of synthetic present‐day observables and infer five parameters: refe...

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Bibliographic Details
Main Authors: S. Agarwal, N. Tosi, P. Kessel, S. Padovan, D. Breuer, G. Montavon
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2021-04-01
Series:Earth and Space Science
Subjects:
inverse problem
mantle convection
Mars
mixture density networks
Online Access:https://doi.org/10.1029/2020EA001484

Internet

https://doi.org/10.1029/2020EA001484

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