Publikationen von Sina Stocker

Stocker, S.; Jung, H.; Csányi, G.; Goldsmith, C. F.; Reuter, K.; Margraf, J.: Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration. Journal of Chemical Theory and Computation 19 (19), S. 6796 - 6804 (2023)

Jung, H.; Sauerland, L.; Stocker, S.; Reuter, K.; Margraf, J.: Machine-learning driven global optimization of surface adsorbate geometries. npj Computational Materials 9, 114 (2023)

Stocker, S.; Gasteiger, J.; Becker, F.; Günnemann, S.; Margraf, J.: How robust are modern graph neural network potentials in long and hot molecular dynamics simulations? Machine Learning: Science and Technology 3 (4), 045010 (2022)

Stocker, S.: Transferability in chemical machine learning. Dissertation, Technische Universität, München (2022)