9 November 2021, Reading Group: Elements of Causal Inference

The reading group is about the book: Peters, Janzing & Schölkopf (2017), Elements of Causal Inference: Foundations and Learning Algorithms, The MIT Press. The book "teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems". It can be openly accessed from the publisher's website.

For our first meeting, we have to read the first three chapters:
1. Statistical and Causal Models (pp. 1-14)
2. Assumptions for Causal Inference (pp. 15-32)
3. Cause-Effect Models (pp. 33-42).

The reading group is held under the supervision of Dr. Katrin Schultz and is organized along with Evan Iatrou (MoL student, evangelos.iat at gmail.com).