Machine Learning Clifford invariants of ADE Coxeter elements

1 code implementation • 29 Sep 2023 • Siqi Chen, Pierre-Philippe Dechant, Yang-Hui He, Elli Heyes, Edward Hirst, Dmitrii Riabchenko

This provides the perfect setup for machine learning, and indeed we see that the datasets can be machine learned to very high accuracy.

Cluster Algebras: Network Science and Machine Learning

1 code implementation • 25 Mar 2022 • Pierre-Philippe Dechant, Yang-Hui He, Elli Heyes, Edward Hirst

Network analysis methods are applied to the exchange graphs for cluster algebras of varying mutation types.

Graph Embedding

Therapeutic Interfering Particles Exploiting Viral Replication and Assembly Mechanisms Show Promising Performance: A Modelling Study

no code implementations • 4 Aug 2021 • Farzad Fatehi, Richard J. Bingham, Pierre-Philippe Dechant, Peter G. Stockley, Reidun Twarock

Defective interfering particles arise spontaneously during a viral infection as mutants lacking essential parts of the viral genome.

Machine-learning a virus assembly fitness landscape

1 code implementation • 13 Jan 2019 • Pierre-Philippe Dechant, Yang-Hui He

Realistic evolutionary fitness landscapes are notoriously difficult to construct.

BIG-bench Machine Learning