Metric learning for kernel ridge regression: assessment of molecular similarity. - Raimon Fabregat; Puck van Gerwen; Matthieu Haeberle; Friedrich Eisenbrand; Clémence Corminboeuf (Mach. Learn. Sci. Technol., 2022)

Repetition-Structure Inference With Formal Prototypes. - Christoph Finkensiep; Matthieu Haeberle; Friedrich Eisenbrand; Markus Neuwirth; Martin Rohrmeier (ISMIR, 2023)

An Improved Bound on Sums of Square Roots via the Subspace Theorem. - Friedrich Eisenbrand; Matthieu Haeberle; Neta Singer (SoCG, 2024)

Integer linear programming for unsupervised training set selection in molecular machine learning. - Matthieu Haeberle; Puck van Gerwen; Rubén Laplaza; Ksenia R. Briling; Jan Weinreich; Friedrich Eisenbrand; Clémence Corminboeuf (CoRR, 2024)