Mitchell A. Wood
Materials Chemistry · 2017–2019
A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 53 citations into it
Whom Mitchell A. Wood trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- J. Behler (in Materials Chemistry)
Papers from Mitchell A. Wood's perspective
Ordered by how strongly the researchers Mitchell A. Wood trusts endorse each paper. Same corpus, a different order for every researcher.
- Accurate Force Field for Molybdenum by Machine Learning Large Materials Data
- Machine learning based interatomic potential for amorphous carbon
- Comparing molecules and solids across structural and alchemical space.
- Computational Materials Science X
- The journal of physical chemistry letters
- Accuracy and transferability of Gaussian approximation potential models for tungsten
- Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons.
- Atom-centered symmetry functions for constructing high-dimensional neural network potentials.
- On representing chemical environments
- Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
Their papers
- A Performance and Cost Assessment of Machine Learning Interatomic Potentials. (2019) — 807 citations
- Quantum-Accurate Molecular Dynamics Potential for Tungsten (2017) — 28 citations