A. De Vita

Materials Chemistry · 2002–2018

A researcher in the Science corpus: 5 papers; trusts 15 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 42 citations into it; #1,900 of 11,513 by trust here, #4,355 by citations
• Atomic and Molecular Physics, and Optics — 26 citations into it; #1,508 of 7,135 by trust here, #1,722 by citations
• Computational Chemistry & Drug Discovery — 15 citations into it
• Computational Theory and Mathematics — 15 citations into it; #7,232 of 12,182 by trust here, #4,199 by citations
• Physical and Theoretical Chemistry — 13 citations into it
• Geophysics — 8 citations into it

Whom A. De Vita trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Radford M. Neal
2. A. P. Bart'ok
3. Yuri Mishin
4. M. Finnis
5. Kevin P. Murphy
6. Matthias Rupp 
7. Gábor Csányi
8. J. Perdew

Who trusts A. De Vita overall

1. Alexander V. Shapeev
2. Evgeny V. Podryabinkin
3. G. P. P. Pun
4. Rohit Batra
5. Yuri Mishin
6. Rampi Ramprasad

Papers from A. De Vita's perspective

Ordered by how strongly the researchers A. De Vita trusts endorse each paper. Same corpus, a different order for every researcher.

1. Generalized neural-network representation of high-dimensional potential-energy surfaces.
2. Fast and accurate modeling of molecular atomization energies with machine learning.
3. Functions of Positive and Negative Type, and their Connection with the Theory of Integral Equations
4. Bio-inspired synthesis of xishacorenes A, B, and C, and a new congener from fuscol
5. Pattern Recognition and Machine Learning
6. Finding Density Functionals with Machine Learning
7. Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces.
8. Learning scheme to predict atomic forces and accelerate materials simulations
9. Generalized Gradient Approximation Made Simple.
10. The formation of molecular clouds in spiral galaxies

Their papers

• Efficient nonparametric n -body force fields from machine learning (2018) — 107 citations
• Low-speed fracture instabilities in a brittle crystal (2008) — 204 citations
• Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces. (2015) — 514 citations
• Accurate interatomic force fields via machine learning with covariant kernels (2016) — 175 citations
• DNA as a Selective Metallization Template (2002) — 272 citations