Library
Chapter 15

Causal Machine Learning

Curated summaries of the key literature behind this chapter — the findings, the methods, and how to put them to work.

13 referenced in this chapter

This chapter Library is for Research-to-Production students

R2P students unlock curated summaries of every key paper behind this chapter — the core findings, the methods, and how to apply them — plus resources we keep adding over time.

Advances in Financial Machine Learning
Marcos Lopez de Prado (2018)
Granger Causality: A Review and Recent Advances
Ali Shojaie and Emily B. Fox (2022)
Identification and Estimation of Local Average Treatment Effects
Guido W. Imbens and Joshua D. Angrist (1994)
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game
Alexander Reisach et al. (2021)
Inference on Treatment Effects After Selection Amongst High-Dimensional Controls
Alexandre Belloni et al. (2012)
plus 8 more references inside
Explore the R2P course