Unified Representation for Machine Learning of Molecules and Crystals

By Haoyan Huo, Matthias Rupp . 2017

52 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yoshua Bengio
2. K. Müller
3. Wojciech Samek
4. Sam Schoenholz
5. Grgoire Montavon
6. Kristof T. Schütt
7. Quoc V. Le
8. Ruslan Salakhutdinov

Citations in the corpus

• Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error. (2017, background): “While finalizing our study, competitive alternatives were introduced 35,36 but have been tested only for energies (and polarizabilities).”
• Exploring chemical compound space with quantum-based machine learning (2019, background): “While both unified [59] as”
• Quantum-chemical insights from interpretable atomistic neural networks (2018, background): “Thus, many-body interactions can be inferred without having to explicitly include angular or higher-order information [16, 41, 42].”