1 citations · 1 across the 4 of their papers we have counts for
5 papers
Set-Valued Policy Learning
Laura Fuentes-Vicente, Mathieu Even, Gaëlle Dormion +3
Conventional treatment policies map patient covariates to a single recommended intervention in order to maximize expected clinical outcomes. Although a rich body of causal inferenc…
Policy learning under constraint: Maximizing a primary outcome while controlling an adverse event
Laura Fuentes-Vicente, Mathieu Even, Gaelle Dormion +2
A medical policy aims to support decision-making by mapping patient characteristics to individualized treatment recommendations. Standard approaches typically optimize a single out…
AdaptiveConformal: An R Package for Adaptive Conformal Inference
Herbert Susmann, Antoine Chambaz, Julie Josse
Conformal Inference (CI) is a popular approach for generating finite sample prediction intervals based on the output of any point prediction method when data are exchangeable. Adap…
Quantile Super Learning for independent and online settings with application to solar power forecasting
Herbert Susmann, Antoine Chambaz
Estimating quantiles of an outcome conditional on covariates is of fundamental interest in statistics with broad application in probabilistic prediction and forecasting. We propose…
Positivity-free Policy Learning with Observational Data
Pan Zhao, Antoine Chambaz, Julie Josse +1
Policy learning utilizing observational data is pivotal across various domains, with the objective of learning the optimal treatment assignment policy while adhering to specific co…