Michael W. Gaultois

According to our database, Michael W. Gaultois authored at least 6 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Probabilistic Isolation of Crystalline Inorganic Phases.

Daniel Ritchie, Michael W. Gaultois, Vladimir V. Gusev, Vitaliy Kurlin, Matthew J. Rosseinsky, Matthew S. Dyer

J. Chem. Inf. Model., 2025

2024

Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials.

Federico Ottomano, John Yannis Goulermas, Vladimir V. Gusev, Rahul Savani, Michael W. Gaultois, Troy D. Manning, Hai Lin, Teresa P. Manzanera, Emmeline G. Poole, Matthew S. Dyer, John B. Claridge, Jon Alaria, Luke M. Daniels, Su Varma, David Rimmer, Kevin Sanderson, Matthew J. Rosseinsky

CoRR, 2024

Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informatics.

Michael Moran, Vladimir V. Gusev, Michael W. Gaultois, Dmytro Antypov, Matthew J. Rosseinsky

CoRR, 2024

2023

Metrics for quantifying isotropy in high dimensional unsupervised clustering tasks in a materials context.

Samantha Durdy, Michael W. Gaultois, Vladimir V. Gusev, Danushka Bollegala, Matthew J. Rosseinsky

CoRR, 2023

2022

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 W. Gaultois, Vladimir V. Gusev, Danushka Bollegala, Matthew J. Rosseinsky

CoRR, 2022

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties.

Andrij Vasylenko, Dmytro Antypov, Vladimir V. Gusev, Michael W. Gaultois, Matthew S. Dyer, Matthew J. Rosseinsky

CoRR, 2022