Accurate machine learning force fields via experimental and simulation data fusion. - Sebastien Röcken; Julija Zavadlav (CoRR, 2023)

Predicting solvation free energies with an implicit solvent machine learning potential. - Sebastien Röcken; Anton F. Burnet; Julija Zavadlav (CoRR, 2024)

chemtrain: Learning deep potential models via automatic differentiation and statistical physics. - Paul Fuchs; Stephan Thaler; Sebastien Röcken; Julija Zavadlav (Comput. Phys. Commun., 2025)

Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements. - Sebastien Röcken; Julija Zavadlav (J. Chem. Inf. Model., 2025)