Matthew J. Rosseinsky

According to our database, Matthew J. Rosseinsky authored at least 6 papers between 2020 and 2024.

Collaborative distances:

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

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

Optimality guarantees for crystal structure prediction.

Vladimir V. Gusev, Duncan Adamson, Argyrios Deligkas, Dmytro Antypov, Christopher M. Collins, Piotr Krysta, Igor Potapov, George R. Darling, Matthew S. Dyer, Paul G. Spirakis, Matthew J. Rosseinsky

Nat., 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

2020

Crystal Structure Prediction via Oblivious Local Search.

Dmytro Antypov, Argyrios Deligkas, Vladimir V. Gusev, Matthew J. Rosseinsky, Paul G. Spirakis, Michail Theofilatos

Proceedings of the 18th International Symposium on Experimental Algorithms, 2020