3 papers
stat.ML2026
Contrast-Free ICA and Causal Inference via Wasserstein Distances to the Gaussian
Félix Laplante, Christophe Ambroise, Pierre Humbert
We study the squared -Wasserstein distance to the standard Gaussian as a non-Gaussianity criterion and use it for linear Independent Component Analysis (ICA) and causal discover…
stat.ME2026
A General Framework for Joint Multi-State Models
Félix Laplante, Christophe Ambroise
Conventional joint modeling approaches generally characterize the relationship between longitudinal biomarkers and discrete event occurrences within terminal, recurring or competin…
stat.ME2025
Causal inference of post-transcriptional regulation timelines from long-read sequencing in Arabidopsis thaliana
Rubén Martos, Christophe Ambroise, Guillem Rigaill
We propose a novel framework for reconstructing the chronology of genetic regulation using causal inference based on Pearl's theory. The approach proceeds in three main stages: cau…