Tobias Morawietz

Atomic and Molecular Physics, and Optics · 2011–2016

A researcher in the Science corpus: 4 papers; trusts 6 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Atomic and Molecular Physics, and Optics — 35 citations into it; #2,612 of 7,135 by trust here, #2,287 by citations
• Materials Chemistry — 32 citations into it; #2,704 of 11,513 by trust here, #5,386 by citations
• Physical and Theoretical Chemistry — 13 citations into it
• Molecular Biology — 6 citations into it
• AI for Physical Sciences — 5 citations into it

Whom Tobias Morawietz trusts overall

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

1. J. Behler
2. Axel D. Becke
3. S. Plimpton
4. Stefan Grimme
5. W. L. Jorgensen
6. Sergei Manzhos
7. Nongnuch Artrith
8. Michele Parrinello
9. D. van der Spoel
10. B. Guillot

Who trusts Tobias Morawietz overall

1. J. Behler
2. Sam Schoenholz
3. Oliver T. Unke
4. Tânia F Cova
5. Michael Gastegger
6. Pavlo O. Dral
7. A. P. Bart'ok
8. A. Pais
9. Rohit Batra
10. Kun Yao

Papers from Tobias Morawietz's perspective

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

1. Generalized neural-network representation of high-dimensional potential-energy surfaces.
2. GROMACS: Fast, flexible, and free
3. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density.
4. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.
5. Water: From Clusters to the Bulk. (Angewandte Chemie)
6. Density-functional exchange-energy approximation with correct asymptotic behavior.
7. Fast parallel algorithms for short-range molecular dynamics
8. Representing potential energy surfaces by high-dimensional neural network potentials
9. and s
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide (2011) — 295 citations
• How van der Waals interactions determine the unique properties of water (2016) — 416 citations
• A density-functional theory-based neural network potential for water clusters including van der Waals corrections. (2013) — 177 citations
• A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges. (2012) — 158 citations