36 citations · 104 across the 9 of their papers we have counts for
4 papers · 1 filter
Generating candidates in global optimization algorithms using complementary energy landscapes
Andreas Møller Slavensky, Mads-Peter V. Christensen, Bjørk Hammer
Global optimization of atomistic structure rely on the generation of new candidate structures in order to drive the exploration of the potential energy surface (PES) in search for…
Atomistic structure search using local surrogate mode
Nikolaj Rønne, Mads-Peter V. Christiansen, Andreas Møller Slavensky +5
We describe a local surrogate model for use in conjunction with global structure search methods. The model follows the Gaussian approximation potential (GAP) formalism and is based…
Atomistic Global Optimization X: A Python package for optimization of atomistic structures
Mads-Peter Verner Christiansen, Nikolaj Rønne, Bjørk Hammer
Modelling and understanding properties of materials from first principles require knowledge of the underlying atomistic structure. This entails knowing the individual identity and…
Generating stable molecules using imitation and reinforcement learning
Søren Ager Meldgaard, Jonas Köhler, Henrik Lund Mortensen +3
Chemical space is routinely explored by machine learning methods to discover interesting molecules, before time-consuming experimental synthesizing is attempted. However, these met…