4 papers · 1 filter
Limits of Learning Linear Dynamics from Experiments
Aybüke Ulusarslan, Niki Kilbertus, Nora Schneider
Learning governing dynamics from data is a common goal across the sciences, yet it is only well-posed when the underlying mechanisms are identifiable. In practice, many data-driven…
Conservative Continuous-Time Treatment Optimization
Nora Schneider, Georg Manten, Niki Kilbertus
We develop a conservative continuous-time stochastic control framework for treatment optimization from irregularly sampled patient trajectories. The unknown patient dynamics are mo…
Generative Intervention Models for Causal Perturbation Modeling
Nora Schneider, Lars Lorch, Niki Kilbertus +2
We consider the problem of predicting perturbation effects via causal models. In many applications, it is a priori unknown which mechanisms of a system are modified by an external…
Anchor Data Augmentation
Nora Schneider, Shirin Goshtasbpour, Fernando Perez-Cruz
We propose a novel algorithm for data augmentation in nonlinear over-parametrized regression. Our data augmentation algorithm borrows from the literature on causality and extends t…