Associate Professor in Machine Learning

Reviewing Consistencies

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In previous posts we have discussed theoretical and conceptual properties of abstractions between causal models, while at the same time implementing code for checking our statements and for running simulations.

In this notebook we take a break in our analysis of abstraction to focus on programming. Since all our code has been accumulated into a single monolithic Abstraction class, we refactor this code into multiple modular classes. This new code implementation will constitute the foundation for future analyses and simulations.

Notebook here

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Scenarios of Confounding

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Causality and causal inference deal with expressing and reasoning about relationships of cause and effects, and structural causal model provide a rigorous formalism to assess causality.