Associate Professor in Machine Learning

Comparing Transformations and Abstractions between Causal Models

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In previous posts we have analyzed how causal models may be related to each other at different levels of abstraction relying on the framework proposed by Rischel and grounded in category theory.

In this notebook we consider a different way to relate causal models via the notion of transformation, as it was proposed earlier by Rubenstein et al.. We consider this alternative definition and we setup a preliminary comparison between abstractions and transformations. We provide a number of examples in order to highlight similarities and differences in the two concepts and in their implications.

Notebook here

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