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#artificial intelligence Preprint Oct 2026

Mapping and Advancing the Scalability-Accuracy Frontier of Nonlinear Causal Discovery

Scalable nonlinear causal discovery requires methods that combine flexible mechanism estimators with efficient search over large graph spaces. Several algorithmic families have been proposed to address this challenge, yet their accuracy-runtime trade-offs remain poorly understood. We empirically compare the four major...

H. Suhr, Sascha Xu, J. Vreeken · 0 citations

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