Causality, Statistics and Machine Learning
Date:
This talk aims at providing an overall understanding of causality, and its implications for modelling, statistics and machine learning. We will highlight some problems of classical machine learning and statistical approaches, and then introduce the solution of casual models using the graphical language of structural causal models. We will then discuss some paradigmatic casual problems and discuss their relationship to machine learning.