David J. Wales

According to our database, David J. Wales authored at least 17 papers between 2010 and 2026.

Collaborative distances:

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

2026

Comparison of Protein-Glycosaminoglycan Interactions in ff14sb/GLYCAM06j-1 and CHARMM36m Force Fields.

Krzysztof K. Bojarski, Patryk A. Wesolowski, Diksha Dewan, Lukasz J. Dziadek, Vilmos Neuman, Bernard R. Brooks, Jacek Czub, Martin Zacharias, Adam K. Sieradzan, David J. Wales

J. Chem. Inf. Model., 2026

2025

Encoding molecular structures in quantum machine learning.

Choy Boy, Edoardo Altamura, Dilhan Manawadu, Ivano Tavernelli, Stefano Mensa, David J. Wales

Mach. Learn. Sci. Technol., 2025

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

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

Physics Inspired Approaches Towards Understanding Gaussian Processes.

Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp, David J. Wales

CoRR, 2023

Physics-Inspired Interpretability Of Machine Learning Models.

Maximilian P. Niroomand, David J. Wales

CoRR, 2023

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

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

2021

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

2020

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

2019

Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins.

Sridhar Neelamraju, David J. Wales, Shachi Gosavi

J. Chem. Inf. Model., 2019

2018

The Loss Surface of XOR Artificial Neural Networks.

Dhagash Mehta, Xiaojun Zhao, Edgar A. Bernal, David J. Wales

CoRR, 2018

2017

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

2016

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

2012

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

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

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