4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
Deconfounding Scores and Representation Learning for Causal Effect Estimation with Weak Overlap
Oscar Clivio, Alexander D'Amour, Alexander Franks +3
Overlap, also known as positivity, is a key condition for causal treatment effect estimation. Many popular estimators suffer from high variance and become brittle when features dif…
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
Oscar Clivio, Avi Feller, Chris Holmes
Reweighting a distribution to minimize a distance to a target distribution is a powerful and flexible strategy for estimating a wide range of causal effects, but can be challenging…
PWSHAP: A Path-Wise Explanation Model for Targeted Variables
Lucile Ter-Minassian, Oscar Clivio, Karla Diaz-Ordaz +2
Predictive black-box models can exhibit high accuracy but their opaque nature hinders their uptake in safety-critical deployment environments. Explanation methods (XAI) can provide…
Neural Score Matching for High-Dimensional Causal Inference
Oscar Clivio, Fabian Falck, Brieuc Lehmann +2
Traditional methods for matching in causal inference are impractical for high-dimensional datasets. They suffer from the curse of dimensionality: exact matching and coarsened exact…