Cecilia Casolo — accepted AI-conference papers

2026

Identifiability Challenges in Sparse Linear Ordinary Differential Equations

Cecilia Casolo, Sören Becker, Niki Kilbertus

ICLR 2026poster

Dynamical systems modeling is a core pillar of scientific inquiry across natural and life sciences. Increasingly, dynamical system models are learned from data, rendering identifiability a paramount concept. For systems that are not identifiable from data, no guarantees can be given about their beha…

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2025

Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes

Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus

ICLR 2025spotlight

Inferring the causal structure underlying stochastic dynamical systems from observational data holds great promise in domains ranging from science and health to finance. Such processes can often be accurately modeled via stochastic differential equations (SDEs), which naturally imply causal relation…

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