Clemens Kauffmann

Materials Chemistry · 2016

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 13 citations into it

Whom Clemens Kauffmann trusts overall

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

1. J. Behler

Papers from Clemens Kauffmann's perspective

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

1. Neural Networks for Pattern Recognition
2. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.
5. Generalized neural-network representation of high-dimensional potential-energy surfaces.
6. Perceptrons
7. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density.
8. GROMACS: Fast, flexible, and free
9. Water: From Clusters to the Bulk. (Angewandte Chemie)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Comparing the accuracy of high-dimensional neural network potentials and the systematic molecular fragmentation method: A benchmark study for all-trans alkanes. (2016) — 52 citations