Inferring material properties of the lower mantle minerals using Mixture Density Networks-Reference-Cited by-同舟云学术

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Inferring material properties of the lower mantle minerals using Mixture Density Networks

Published:2021-10 Issue: Volume:319 Page:106784
ISSN:0031-9201
Container-title:Physics of the Earth and Planetary Interiors
language:en
Short-container-title:Physics of the Earth and Planetary Interiors

Author:

Rijal Ashim^ORCID,Cobden Laura,Trampert Jeannot,Jackson Jennifer M.,Valentine Andrew^ORCID

Publisher

Elsevier BV

Subject

Space and Planetary Science,Physics and Astronomy (miscellaneous),Geophysics,Astronomy and Astrophysics

Reference97 articles.

1. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems;Abadi,2015

2. Using pattern recognition to infer parameters governing mantle convection;Atkins;Phys. Earth Planet. Inter.,2016

3. Neural Networks for Pattern Recognition;Bishop,1995

4. Mixture Density Networks;Bishop,1994

5. Inferring upper-mantle temperatures from seismic velocities;Cammarano;Phys. Earth Planet. Inter.,2003

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Tomographic filtering of shear and compressional wave models reveals uncorrelated variations in the lowermost mantle;Geophysical Journal International;2023-04-27

2. Shear properties of MgO inferred using neural networks;European Journal of Mineralogy;2023-01-17

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