jvpoulos/causal-ml
Must-read papers and resources related to causal inference and machine (deep) learning
This project offers a curated collection of recent research papers and resources focused on applying machine learning techniques to understand cause-and-effect relationships. It helps researchers, data scientists, and analysts who need to measure the impact of interventions or policies. The collection provides categorized lists of academic papers, code libraries, datasets, and courses, making it easier to stay updated on cutting-edge methods.
749 stars. No commits in the last 6 months.
Use this if you are a researcher or data scientist looking for a comprehensive, organized list of academic papers and resources at the intersection of causal inference and machine learning.
Not ideal if you are looking for an off-the-shelf software tool or code to directly implement causal machine learning models without diving into the underlying research.
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Nov 23, 2022
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