2 citations · 2 across the 2 of their papers we have counts for
3 papers
Learning atomic forces from uncertainty-calibrated adversarial attacks
Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson +3
Adversarial approaches, which intentionally challenge machine learning models by generating difficult examples, are increasingly being adopted to improve machine learning interatom…
On the equivalence of the hybrid particle-field and Gaussian core models
Morten Ledum, Samiran Sen, Sigbjørn Løland Bore +1
Hybrid particle-field molecular dynamics is a molecular simulation strategy wherein particles couple to a density field instead of through ordinary pair potentials. Traditionally c…
Automated Determination of Hybrid Particle-Field Parameters by Machine Learning
Morten Ledum, Sigbjørn Løland Bore, Michele Cascella
The hybrid particle-field molecular dynamics method is an efficient alternative to standard particle-based coarse grained approaches. In this work, we propose an automated protocol…