One of the most important research areas in Machine Learning is to build prescriptive models. This requires understanding and measurement of the causal impact of any proposed treatment, followed by designing optimal strategy based on such causal ...

The workshop's rationale stems from the escalating interest in causal inference and machine learning methodologies within various industrial contexts. This surge in demand underscores the importance for both scholars and practitioners to exchange ...

Causal machine learning (ML) algorithms recover graphical structures that tell us something about cause-and-effect relationships. The causal representation provided by these algorithms enables transparency and explainability, which is necessary ...