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insight - Kernel-based CI Test for Causal Discovery
Signature Kernel Conditional Independence Tests for Causal Discovery in Stochastic Processes
The author develops a kernel-based test of conditional independence on path-space using signature kernels, demonstrating superior performance compared to existing approaches. The approach enables constraint-based causal discovery in acyclic stochastic dynamical systems.
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes: A Comprehensive Analysis
Studying the effectiveness of a kernel-based conditional independence test in causal discovery for stochastic processes.
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