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New framework connects causal graphs and do-calculus to SDEs · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a framework for understanding causal graphs and do-calculus within the context of stochastic differential equations (SDEs). This work establishes the sigma-separation Markov property and do-calculus for SDEs, providing a causal interpretation of graphs where the absence of a directed path signifies no causal effect. The framework also introduces time-split systems to analyze subsampled time-series and Granger non-causality, and discusses the applicability of constraint-based causal discovery algorithms like PC, FCI, CCD, and CCI to SDEs. AI

IMPACT Advances theoretical understanding of causal inference in continuous-time dynamical systems, potentially impacting AI research in areas like reinforcement learning and time-series analysis.

RANK_REASON Academic paper published on arXiv detailing a new theoretical framework for causal inference in SDEs.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework connects causal graphs and do-calculus to SDEs · 2 sources tracked

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Academic paper published on arXiv detailing a new theoretical framework for causal inference in SDEs.
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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Philip Boeken, Joris M. Mooij ·

    Causal Graphs, Markov Properties and Do-calculus for Stochastic Differential Equations

    arXiv:2607.12140v1 Announce Type: cross Abstract: Stochastic differential equations (SDEs) are widely used to model continuous-time dynamical systems, but graphical causal models for them are not yet well-understood. We consider systems of causal SDEs that are equipped with an ex…

  2. arXiv stat.ML TIER_1 English(EN) · Joris M. Mooij ·

    Causal Graphs, Markov Properties and Do-calculus for Stochastic Differential Equations

    Stochastic differential equations (SDEs) are widely used to model continuous-time dynamical systems, but graphical causal models for them are not yet well-understood. We consider systems of causal SDEs that are equipped with an explicit causal semantics. We pose solvability condi…

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