84 citations · 235 across the 5 of their papers we have counts for
5 papers
Causal Modeling of Dynamical Systems
Stephan Bongers, Tineke Blom, Joris M. Mooij
Dynamical systems are widely used in science and engineering to model systems consisting of several interacting components. Often, they can be given a causal interpretation in the…
Causal Consistency of Structural Equation Models
Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers +4
Complex systems can be modelled at various levels of detail. Ideally, causal models of the same system should be consistent with one another in the sense that they agree in their p…
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Sara Magliacane, Thijs van Ommen, Tom Claassen +3
An important goal common to domain adaptation and causal inference is to make accurate predictions when the distributions for the source (or training) domain(s) and target (or test…
Foundations of Structural Causal Models with Cycles and Latent Variables
Stephan Bongers, Patrick Forré, Jonas Peters +1
Structural causal models (SCMs), also known as (nonparametric) structural equation models (SEMs), are widely used for causal modeling purposes. In particular, acyclic SCMs, also kn…
From Deterministic ODEs to Dynamic Structural Causal Models
Paul K. Rubenstein, Stephan Bongers, Bernhard Schoelkopf +1
Structural Causal Models are widely used in causal modelling, but how they relate to other modelling tools is poorly understood. In this paper we provide a novel perspective on the…