2 citations · 2 across the 2 of their papers we have counts for
6 papers
Causality and independence in perfectly adapted dynamical systems
Tineke Blom, Joris M. Mooij
Perfect adaptation in a dynamical system is the phenomenon that one or more variables have an initial transient response to a persistent change in an external stimulus but revert t…
Robustness of Model Predictions under Extension
Tineke Blom, Joris M. Mooij
Mathematical models of the real world are simplified representations of complex systems. A caveat to using mathematical models is that predicted causal effects and conditional inde…
Conditional independences and causal relations implied by sets of equations
Tineke Blom, Mirthe M. van Diepen, Joris M. Mooij
Real-world complex systems are often modelled by sets of equations with endogenous and exogenous variables. What can we say about the causal and probabilistic aspects of variables…
An Upper Bound for Random Measurement Error in Causal Discovery
Tineke Blom, Anna Klimovskaia, Sara Magliacane +1
Causal discovery algorithms infer causal relations from data based on several assumptions, including notably the absence of measurement error. However, this assumption is most like…
Beyond Structural Causal Models: Causal Constraints Models
Tineke Blom, Stephan Bongers, Joris M. Mooij
Structural Causal Models (SCMs) provide a popular causal modeling framework. In this work, we show that SCMs are not flexible enough to give a complete causal representation of dyn…
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…