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cs.AI2024★ 1 cited
Large Language Models for Constrained-Based Causal Discovery
Kai-Hendrik Cohrs, Gherardo Varando, Emiliano Diaz +2
Causality is essential for understanding complex systems, such as the economy, the brain, and the climate. Constructing causal graphs often relies on either data-driven or expert-d…
stat.ML2024
Recovering Latent Confounders from High-dimensional Proxy Variables
Nathan Mankovich, Homer Durand, Emiliano Diaz +2
Detecting latent confounders from proxy variables is an essential problem in causal effect estimation. Previous approaches are limited to low-dimensional proxies, sorted proxies, a…