Geometry optimisation based on machine learning

Johannes Kästner's group at the University of Stuttgart have extended DL-FIND to use Gaussian-process regression (GPR) to search for minima, transition states, and reaction paths.

Energies and gradients during the optimisation trajectory enter the GPR algorithms, which build up a surrogate surface that aids the optimisation. The resulting algorithm requires fewer steps than traditional approaches, especially for transition states and reaction paths. Moreover, Cartesian coordinates and, recently, also internal coordinates can be used.

Subscribe to RSS - DL-FIND