26 citations · 26 across the 2 of their papers we have counts for
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…
cs.LG2022★ 26 cited
Random projections and Kernelised Leave One Cluster Out Cross-Validation: Universal baselines and evaluation tools for supervised machine learning for materials properties
Samantha Durdy, Michael Gaultois, Vladimir Gusev +2
With machine learning being a popular topic in current computational materials science literature, creating representations for compounds has become common place. These representat…