36 citations · 104 across the 9 of their papers we have counts for
3 papers · 1 filter
Augmentation of Universal Potentials for Broad Applications
Joe Pitfield, Florian Brix, Zeyuan Tang +4
Universal potentials open the door for DFT level calculations at a fraction of their cost. We find that for application to systems outside the scope of its training data, CHGNet\ci…
Efficient ensemble uncertainty estimation in Gaussian Processes Regression
Mads-Peter Verner Christiansen, Nikolaj Rønne, Bjørk Hammer
Reliable uncertainty measures are required when using data based machine learning interatomic potentials (MLIPs) for atomistic simulations. In this work, we propose for sparse Gaus…
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…