Symmetrization of the AMBER and CHARMM force fields. - Edyta Malolepsza; Birgit Strodel; Mey Khalili; Semen Trygubenko; Szilard N. Fejer; David J. Wales (J. Comput. Chem., 2010)

The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein. - Michael C. Prentiss; David J. Wales; Peter G. Wolynes (PLoS Comput. Biol., 2010)

Erratum: Symmetrization of the AMBER and CHARMM force fields [J. Comp. Chem. 31, 1402]. - Edyta Malolepsza; Birgit Strodel; Mey Khalili; Semen Trygubenko; Szilard N. Fejer; Joanne M. Carr; David J. Wales (J. Comput. Chem., 2012)

QTAIM and stress tensor interpretation of the (H2O)5 potential energy surface. - Tianlv Xu; James Farrell; Yuning Xu; Roya Momen; Steven R. Kirk; Samantha Jenkins; David J. Wales (J. Comput. Chem., 2016)

Perspective: Energy Landscapes for Machine Learning. - Andrew J. Ballard; Ritankar Das; Stefano Martiniani; Dhagash Mehta; Levent Sagun; Jacob D. Stevenson; David J. Wales (CoRR, 2017)

The Loss Surface of XOR Artificial Neural Networks. - Dhagash Mehta; Xiaojun Zhao; Edgar A. Bernal; David J. Wales (CoRR, 2018)

Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins. - Sridhar Neelamraju; David J. Wales; Shachi Gosavi (J. Chem. Inf. Model., 2019)

Perspective: new insights from loss function landscapes of neural networks. - Sathya R. Chitturi; Philipp C. Verpoort; Alpha A. Lee; David J. Wales (Mach. Learn. Sci. Technol., 2020)

Development of ReaxFF Reactive Force Field for Aqueous Iron-Sulfur Clusters with Applications to Stability and Reactivity in Water. - Evgeny Moerman; David Furman; David J. Wales (J. Chem. Inf. Model., 2021)

Characterising the area under the curve loss function landscape. - Maximilian P. Niroomand; Conor T. Cafolla; John W. R. Morgan; David J. Wales (Mach. Learn. Sci. Technol., 2022)

On the capacity and superposition of minima in neural network loss function landscapes. - Maximilian P. Niroomand; John W. R. Morgan; Conor T. Cafolla; David J. Wales (Mach. Learn. Sci. Technol., 2022)

Physics-Inspired Interpretability Of Machine Learning Models. - Maximilian P. Niroomand; David J. Wales (CoRR, 2023)

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)

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