  We implemented a gradient-based algorithm for transition state search which
uses Gaussian process regression. Besides a description of the algorithm, we
provide a method to find the starting point for the optimization if only the
reactant and product minima are known. We perform benchmarks on 27 test systems
against the dimer method and partitioned rational function optimization as
implemented in the DL-FIND library. We found the new optimizer to significantly
decrease the number of required energy and gradient evaluations.
