Tenured Faculty, CISPA Helmholtz Center for Information Security
2 papers at NeurIPS 2025
We propose a fully differentiable architecture for learning an interpretable rule list classifier.
Given a mixture of samples from unobserved subpopulations with distinct underlying causal mechanisms, we give results on identification and discovery of causal graph with latent mixing variables.
