Hillary Hauger — accepted AI-conference papers

2025

ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization

Philipp Scholl, Katharina Bieker, Hillary Hauger, Gitta Kutyniok

ICLR 2025poster

The problem of symbolic regression (SR) arises in many different applications, such as identifying physical laws or deriving mathematical equations describing the behavior of financial markets from given data. Various methods exist to address the problem of SR, often based on genetic programming. Ho…

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2025

Robust Identifiability for Symbolic Recovery of Differential Equations

Hillary Hauger, Philipp Scholl, Gitta Kutyniok

ICASSP 2025accepted

Recent advancements in machine learning have transformed the discovery of physical laws, moving from manual derivation to data-driven methods that simultaneously learn both the structure and parameters of governing equations. This shift introduces new challenges regarding the validity of the discove…

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