Robust Model-Free Identification of the Causal Networks Underlying Complex Nonlinear Systems

Robust Model-Free Identification of the Causal Networks Underlying Complex Nonlinear Systems

Inferring causal networks from noisy observations is of vital importance in various fields. Due to the complexity of system modeling, the way in which universal and feasible inference algorithms are studied is a key challenge for network reconstruction. In this study, without any assumptions, we dev...

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Bibliographic Details
Main Authors: Guanxue Yang, Shimin Lei, Guanxiao Yang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Entropy
Subjects:
model-free
data-driven
causal inference
Granger causality
nonlinear dynamics
Online Access:https://www.mdpi.com/1099-4300/26/12/1063
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https://www.mdpi.com/1099-4300/26/12/1063

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