Max-Planck-Institut f¨ur Kohlenforschung

Atomic and Molecular Physics, and Optics · 2015

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Atomic and Molecular Physics, and Optics — 12 citations into it
• Organic Chemistry — 10 citations into it

Whom Max-Planck-Institut f¨ur Kohlenforschung trusts

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

1. James J. P. Stewart (in Atomic and Molecular Physics, and Optics)
2. David Ruppert (in Evaluation & Benchmarks)

Papers from Max-Planck-Institut f¨ur Kohlenforschung's perspective

Ordered by how strongly the researchers Max-Planck-Institut f¨ur Kohlenforschung trusts endorse each paper. Same corpus, a different order for every researcher.

1. Virtual screening: an endless staircase?
2. Fast and accurate modeling of molecular atomization energies with machine learning.
3. Chemical space
4. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
5. Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies.
6. Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
7. Click Chemistry: Diverse Chemical Function from a Few Good Reactions. (Angewandte Chemie)
8. Machine learning of molecular electronic properties in chemical compound space
9. Challenges for density functional theory. (Chemical Reviews)
10. Functional designed to include surface effects in self-consistent density functional theory

Their papers

• Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. (2015) — 794 citations