Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

The Arctic sea ice has retreated rapidly in the past few decades, which is believed to be driven by various dynamic and thermodynamic processes in the atmosphere. The newly open water resulted from sea ice decline in turn exerts large influence on the atmosphere. Therefore, this study aims to invest...

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Bibliographic Details
Main Authors: Yiyi Huang, Matthäus Kleindessner, Alexey Munishkin, Debvrat Varshney, Pei Guo, Jianwu Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Big Data
Subjects:
causality discovery
time series
arctic sea ice
temporal causality discovery framework
non-combinatorial optimization via trace exponential and augmented lagrangian for structure learning
directed acyclic graph-graph neural networks
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2021.642182/full

Internet

https://www.frontiersin.org/articles/10.3389/fdata.2021.642182/full

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