Δ-Machine Learning Beyond DFT: from Phase Transitions to Quantum Paraelectricity and CO Adsorption
Carla Verdi, Georg Kresse
Now On Demand
This talk will discuss the on-the-fly learning technique implemented in VASP, based on molecular dynamics and Bayesian
inference, and a Δ-machine learning approach.
The UGM Plenary sessions cover a broad range of research and modeling areas. This research fuels the development of Materials Design software, guides the user experience, and enriches its scientific foundation.
Register for the UGM for access to all Plenary talks.