Causation and intervention

By Mathias Frisch. 2014

66 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Law, Causal Inference & Discovery

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Citations in the corpus

Differentiable Causal Discovery from Interventional Data (2020, background): “The general type of interventions described in (2) are called imperfect (or soft, parametric) [36, 7, 8].”
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions (2019, background): “Related Work: Learning causal graphs from a combination of observational and interventional data has been studied in the literature [3, 11, 7, 20, 8, 12, 23].”
Learning Causal Structures Using Regression Invariance (2017, background): “In this setting, the most common identiﬁcation procedure considers that the variables whose distributions have varied are the descendants of the intervened variable and hence the causal structure is reconstructed by performing interventions on different variables in the system [4, 11].”
Algorithmic Recourse: from Counterfactual Explanations to Interventions (2020, background): “While intuitive appealing and powerful, structural interventions are in many ways the simplest type of interventions, and their “simplicity comes at a price: foregoing the possibility of modeling many situations re-alisitically” (Korb et al., 2004; Eberhardt, 2007).”
Learning Causal Graphs with Small Interventions (2015, background): “Furthermore [3] shows that the set of interventions to fully identify a causal DAG must satisfy a speciﬁc set of combinatorial conditions called a separating system 1 , when the intervention size is not constrained or is 1.”