Computational Theoretical Chemistry TRIZ Cases
- ML Force Field Training With Off-Equilibrium Data Sampling
High-uncertainty off-equilibrium sampling improves ML force field accuracy across temperature and pressure ranges without full ab initio cost.
High-uncertainty off-equilibrium sampling improves ML force field accuracy across temperature and pressure ranges without full ab initio cost.