I finished my economics Ph.D. in the summer of 2022, a few months before ChatGPT was released. I did not know it at the time, but my cohort was the last to graduate under the old rules. The empirical ...
“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
Causal inference has been increasingly essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional ...
Dr Hajk-Georg Drost is a Principal Investigator within the Division of Computational Biology. He studied computer science and bioinformatics with a strong focus on statistical learning, machine ...
The goal of this repository is to provide a curated list of resources in Causal Reinforcement Learning (RL). If you have any suggestions (missing papers, tutorials, typos, or amazing blog posts), ...
For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...
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