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An overview of the quantitative causality analysis and causal graph reconstruction based on a rigorous formalism of information flow
Published 31 Dec 2021 in eess.SY, cs.AI, cs.SY, and physics.data-an | (2112.14839v1)
Abstract: Inference of causal relations from data now has become an important field in artificial intelligence. During the past 16 years, causality analysis (in a quantitative sense) has been developed independently in physics from first principles. This short note is a brief summary of this line of work, including part of the theory and several representative applications.
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