Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors

2 code implementations • 15 May 2019 • Peter Bjørn Jørgensen, Estefanía Garijo del Río, Mikkel N. Schmidt, Karsten Wedel Jacobsen

The possibilities for prediction in a realistic computational screening setting is investigated on a dataset of 5976 ABSe$_3$ selenides with very limited overlap with the OQMD training set.

BIG-bench Machine Learning Formation Energy +3