Machine Learning for Atomic Forces in a Crystalline Solid: Transferability to Various Temperatures

Teppei Suzuki, Ryo Tamura, Tsuyoshi Miyazaki

Recently, machine learning has emerged as an alternative, powerful approach for predicting quantum-mechanical properties of molecules and solids. Here, using kernel ridge regressio…