James R. Kermode
0000-0001-6755-6271
Publication & Citation Trends
Publications
0 total
Efficient and accurate spatial mixing of machine learned interatomic potentials for materials science
Cited by 1
Semantic Scholar
Bayesian selection for efficient MLIP dataset selection
Cited by 0
Semantic Scholar
Bayesian regression-based continuum-particle method for low-speed rarefied flow: Application to unsteady Poiseuille flow
Cited by 2
Semantic Scholar
Uncertainty quantification in atomistic simulations of silicon using interatomic potentials. OA
Cited by 7
Semantic Scholar
matscipy: materials science at the atomic scale with Python OA
Cited by 21
Semantic Scholar
A posteriori error estimate and adaptivity for QM/MM models of crystalline defects OA
Cited by 2
Semantic Scholar
Integrated workflows and interfaces for data-driven semi-empirical electronic structure calculations. OA
Cited by 4
Semantic Scholar
ACEpotentials.jl: A Julia implementation of the atomic cluster expansion. OA
Cited by 49
Semantic Scholar
Gaussian approximation potentials: Theory, software implementation and application examples. OA
Cited by 62
Semantic Scholar
Collinear-spin machine learned interatomic potential for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Fe</mml:mi><mml:mn>7</mml:mn></mml:msub><mml:msub><mml:mi>Cr</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mi>Ni</mml:mi></mml:mrow></mml:math> alloy OA
Cited by 1
Semantic Scholar
Research Topics
Machine Learning in Materials Science
(41)
X-ray Diffraction in Crystallography
(12)
Computational Drug Discovery Methods
(11)
High-pressure geophysics and materials
(9)
Microstructure and mechanical properties
(8)
Affiliations
Rutherford Appleton Laboratory
United States Naval Research Laboratory
Science and Technology Facilities Council
King's College London
University of Cambridge