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Sagan

Paper

Function-Valued Causal Influence in Nonlinear Time Series

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AI summary

arXiv:2605. 26408v1 Announce Type: cross Abstract: Causal discovery in time series is increasingly performed using nonlinear machine-learning models, yet the resulting causal relationships are almost always summarized by scalar edge scores.