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stat.ML2024
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees
Joseph Janssen, Vincent Guan, Elina Robeva
Scientists frequently prioritize learning from data rather than training the best possible model; however, research in machine learning often prioritizes the latter. Marginal contr…
stat.ML2024
Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding
Daniela Schkoda, Elina Robeva, Mathias Drton
We consider linear non-Gaussian structural equation models that involve latent confounding. In this setting, the causal structure is identifiable, but, in general, it is not possib…