Publikationen SIMPLAIX
2023
- Fedorov R, Gryn’ova G (2023). Unlocking the Potential: Predicting Redox Behavior of Organic Molecules, from Linear Fits to Neural Networks, J. Chem. Theory Comput. 19(15):4796-4814 1685
- Remme R, Kaczun T, Scheurer M, Dreuw A, Hamprecht FA (2023). KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory, arXiv,physics.chem-ph,2305.13316 1688
2022
- Reiser P, Neubert M, Eberhard A, Torresi L, Zhou C, Shao C, Metni H, Hoesel Cv, Schopmans H, Sommer T, Friederich P (2022). Graph neural networks for materials science and chemistry, Commun Mater 3(1),93 1686
- Lippmann P, Sanmartín EF, Hamprecht FA (2022). Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources, arXiv,cs.LG,2210.07702 1689
