39 citations · 39 across the 1 of their papers we have counts for
4 papers
Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informatics
Michael Moran, Vladimir V. Gusev, Michael W. Gaultois +2
The scarcity of property labels remains a key challenge in materials informatics, whereas materials data without property labels are abundant in comparison. By pretraining supervis…
Pushing the Pareto front of band gap and permittivity: ML-guided search for dielectric materials
Janosh Riebesell, T. Wesley Surta, Rhys Goodall +2
Materials with high-dielectric constant easily polarize under external electric fields, allowing them to perform essential functions in many modern electronic devices. Their practi…
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…
Structural distortion below the Néel temperature in spinel GeCoO
Phillip T. Barton, Moureen C. Kemei, Michael W. Gaultois +5
A structural phase transition from cubic to tetragonal 4/ symmetry with 1 is observed at = 16 K in spinel GeCoO below the Néel…