K-means landscapes: exploring clustering solution spaces using energy landscape theory - Luke Dicks (2021)

Physics Inspired Approaches Towards Understanding Gaussian Processes. - Maximilian P. Niroomand; Luke Dicks; Edward O. Pyzer-Knapp; David J. Wales (CoRR, 2023)

Evolution of K-means solution landscapes with the addition of dataset outliers and a robust clustering comparison measure for their analysis. - Luke Dicks; David J. Wales (CoRR, 2023)

TopSearch: a Python package for topographical analysis of machine learning models and physical systems. - Luke Dicks; Edward O. Pyzer-Knapp (J. Open Source Softw., 2024)

Explainable Gaussian processes: a loss landscape perspective. - Maximilian P. Niroomand; Luke Dicks; Edward O. Pyzer-Knapp; David J. Wales (Mach. Learn. Sci. Technol., 2024)

Refining embeddings with fill-tuning: data-efficient generalised performance improvements for materials foundation models. - Matthew P. Wilson; Edward O. Pyzer-Knapp; Nicolas Galichet; Luke Dicks (CoRR, 2025)