no code implementations • 21 Jan 2020 • Carlos Fernández-Loría, Foster Provost, Xintian Han
We examine counterfactual explanations for explaining the decisions made by model-based AI systems.
1 code implementation • 24 Apr 2020 • Carlos Fernández-Loría, Foster Provost, Jesse Anderton, Benjamin Carterette, Praveen Chandar
This study presents a systematic comparison of methods for individual treatment assignment, a general problem that arises in many applications and has received significant attention from economists, computer scientists, and social scientists.
no code implementations • 8 Apr 2021 • Carlos Fernández-Loría, Foster Provost
Recently, we have seen an acceleration of research related to CDM and causal effect estimation (CEE) using machine-learned models.
no code implementations • 25 Jun 2022 • Carlos Fernández-Loría, Jorge Loría
We present three valuable causal interpretations of these scores: effect estimation (EE), effect ordering (EO), and effect classification (EC).