2 papers
stat.ML2024
On the Nonconvexity of Push-Forward Constraints and Its Consequences in Machine Learning
Lucas de Lara, Mathis Deronzier, Alberto González-Sanz +1
The push-forward operation enables one to redistribute a probability measure through a deterministic map. It plays a key role in statistics and optimization: many learning problems…
math.ST2023
A clarification on the links between potential outcomes and do-interventions
Lucas de Lara
Most of the scientific literature on causal modeling considers the structural framework of Pearl and the potential-outcome framework of Rubin to be formally equivalent, and therefo…