[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"
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Updated
Oct 19, 2023 - Python
[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"
📦 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling
🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation
R package for the estimation of causal effects.
Estimation of causal effects with small data in the presence of trapdoor variables
Collection of datasets for causal tasks.
"Causal Effect Estimation" research internship of Thierry Rioual, supervised by Pierre-Henri Wuillemin (Sorbonne University & LIP6)
Second assignment for Artificial Intelligence course @USI19/20.
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