2 papers
cs.LG2023
Metrics for quantifying isotropy in high dimensional unsupervised clustering tasks in a materials context
Samantha Durdy, Michael W. Gaultois, Vladimir Gusev +2
Clustering is a common task in machine learning, but clusters of unlabelled data can be hard to quantify. The application of clustering algorithms in chemistry is often dependant o…
cond-mat.mtrl-sci2022
Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties
Andrij Vasylenko, Dmytro Antypov, Vladimir Gusev +3
Fundamental differences between materials originate from the unique nature of their constituent chemical elements. Before specific differences emerge according to the precise ratio…