Deep‐Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic‐Climate Data From Moxa Geodynamic Observatory

Deep‐Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic‐Climate Data From Moxa Geodynamic Observatory

Abstract Highly sensitive laser strainmeters at Moxa Geodynamic Observatory (MGO) measure motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters installed in the gallery of the observatory is relatively low, the recorded time series are strongly influenced b...

Full description

Saved in:
Bibliographic Details
Main Authors: Wasim Ahmad, Valentin Kasburg, Nina Kukowski, Maha Shadaydeh, Joachim Denzler
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2024-10-01
Series:Earth and Space Science
Subjects:
causal inference
tectonic‐climate time‐series
deep learning
Online Access:https://doi.org/10.1029/2023EA003430
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items