Machine Learning for Causal Inference in Observational Studies
Summary
Using ML to address causal inference challenges in observational studies where randomized controlled trials aren't feasible. Methods include Random Causal Forests, Representation Learning, Bayesian Inference, and Causal Graphs to predict counterfactuals.
Themes
Keywords
causal inference, observational studies, counterfactual, causal graphs, Bayesian inference
Poster
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