3 papers
cs.AI2023
Quantifying Consistency and Information Loss for Causal Abstraction Learning
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas
Structural causal models provide a formalism to express causal relations between variables of interest. Models and variables can represent a system at different levels of abstracti…
cs.AI2022
Towards Computing an Optimal Abstraction for Structural Causal Models
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas
Working with causal models at different levels of abstraction is an important feature of science. Existing work has already considered the problem of expressing formally the relati…
cs.AI2022
Abstraction between Structural Causal Models: A Review of Definitions and Properties
Fabio Massimo Zennaro
Structural causal models (SCMs) are a widespread formalism to deal with causal systems. A recent direction of research has considered the problem of relating formally SCMs at diffe…