Theoretical Aspects of Cyclic Structural Causal Models

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Causal Models for Dynamical Systems (2020, methodology): “Bongers et al. [2016] give measure theoretic details underlying the construction of SCMs.”
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions (2017, background): “There could be cyclic dependencies, for example due to feedback loops, but for simplicity of exposition we will discuss only the acyclic case here, noting that the extension to the cyclic case is straightforward given recent theoretical advances on cyclic SCMs [Bongers et al., 2018].”
From Deterministic ODEs to Dynamic Structural Causal Models (2016, background): “While it is well understood how an SCM induces a statistical model (Bongers et al., 2018), much less is known about how a differential equation model—our most fundamental level of modelling—can imply an SCM in the first place.”
Fairness in Machine Learning (2020, background): “See, work by Bongers et al.196 196 S. Bongers, J. Peters, B. Schölkopf, and J.M. Mooij, “Theoretical Aspects of Cyclic Structural Causal Models,” arXiv.org Preprint arXiv:1611.06221v2 (2018). on extending the structural causal model perspective to cyclic models.”
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders (2018, unknown): “1), or more generally if the cycles are “uniquely solvable” (see [3, 12]).”