no code implementations • 26 Sep 2023 • Stavros Gerolymatos, Xenophon Evangelopoulos, Vladimir Gusev, John Y. Goulermas
Dimensionality reduction (DR) is one of the key tools for the visual exploration of high-dimensional data and uncovering its cluster structure in two- or three-dimensional spaces.
no code implementations • 25 May 2023 • Samantha Durdy, Michael W. Gaultois, Vladimir Gusev, Danushka Bollegala, Matthew J. Rosseinsky
Using fractional anisotropy, a common method used in medical imaging for comparison, we then expand these measures to examine the average isotropy of a set of clusters.
1 code implementation • 17 Jun 2022 • Samantha Durdy, Michael Gaultois, Vladimir Gusev, Danushka Bollegala, Matthew J. Rosseinsky
We also find that the radial basis function improves the linear separability of chemical datasets in all 10 datasets tested and provide a framework for the application of this function in the LOCO-CV process to improve the outcome of LOCO-CV measurements regardless of machine learning algorithm, choice of metric, and choice of compound representation.
1 code implementation • 2 Feb 2022 • Andrij Vasylenko, Dmytro Antypov, Vladimir Gusev, Michael W. Gaultois, Matthew S. Dyer, Matthew J. Rosseinsky
Before specific differences emerge according to the precise ratios of elements in a given crystal structure, a material can be represented by the set of its constituent chemical elements.
1 code implementation • 27 Mar 2020 • Dmytro Antypov, Argyrios Deligkas, Vladimir Gusev, Matthew J. Rosseinsky, Paul G. Spirakis, Michail Theofilatos
In addition, due to the chemical expertise involved in the parameter-tuning, these approaches can be {\em biased} towards previously-known crystal structures.
Computational Engineering, Finance, and Science