41 citations · 68 across the 26 of their papers we have counts for
9 papers · 1 filter
Teleological Inference in Structural Causal Models via Intentional Interventions
Dario Compagno, Fabio Massimo Zennaro
Structural causal models (SCMs) were conceived to formulate and answer causal questions. This paper shows that SCMs can also be used to formulate and answer teleological questions,…
Multi-Level Causal Embeddings
Willem Schooltink, Fabio Massimo Zennaro
Abstractions of causal models allow for the coarsening of models such that relations of cause and effect are preserved. Whereas abstractions focus on the relation between two model…
Aligning Graphical and Functional Causal Abstractions
Willem Schooltink, Fabio Massimo Zennaro
Causal abstractions allow us to relate causal models on different levels of granularity. To ensure that the models agree on cause and effect, frameworks for causal abstractions def…
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…
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei +2
An abstraction can be used to relate two structural causal models representing the same system at different levels of resolution. Learning abstractions which guarantee consistency…
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…
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…
Counterfactually Fair Prediction Using Multiple Causal Models
Fabio Massimo Zennaro, Magdalena Ivanovska
In this paper we study the problem of making predictions using multiple structural casual models defined by different agents, under the constraint that the prediction satisfies the…
Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation
Fabio Massimo Zennaro, Magdalena Ivanovska
In this paper we consider the problem of combining multiple probabilistic causal models, provided by different experts, under the requirement that the aggregated model satisfy the…