most citedOn the Robustness of Machine Learning Models in Predicting Thermodynamic Properties: a Case of Searching for New Quasicrystal Approximants

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing physics.comp-phShow all

1 paper · 1 filter

physics.comp-ph2024★ 1 cited

On the Robustness of Machine Learning Models in Predicting Thermodynamic Properties: a Case of Searching for New Quasicrystal Approximants

Fedor S. Avilov, Roman A. Eremin, Semen A. Budennyy +1

Despite an artificial intelligence-assisted modeling of disordered crystals is a widely used and well-tried method of new materials design, the issues of its robustness, reliabilit…