Neural network approach to quantum-chemistry data: accurate prediction of density functional theory energies.

By Roman M. Balabin, Ekaterina I. Lomakina. 2009

162 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry

How researchers see this paper

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

In Computational Theory and Mathematics

1. Alán Aspuru-Guzik
2. Rafael Gómez‐Bombarelli
3. Jorge Aguilera-Iparraguirre
4. Edward O. Pyzer-Knapp
5. Changwon Suh
6. José Miguel Hernández-Lobato
7. Ryan-Rhys Griffiths
8. Tommi S. Jaakkola

In Materials Chemistry

1. Alán Aspuru-Guzik
2. Rafael Gómez‐Bombarelli
3. Jorge Aguilera-Iparraguirre
4. Edward O. Pyzer-Knapp
5. José Miguel Hernández-Lobato
6. Ryan-Rhys Griffiths
7. Tommi S. Jaakkola
8. Regina Barzilay

In Organic Chemistry

1. Alán Aspuru-Guzik
2. Jorge Aguilera-Iparraguirre
3. Edward O. Pyzer-Knapp
4. Rafael Gómez‐Bombarelli
5. Changwon Suh

Citations in the corpus

• What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery (2015, methodology): “In organic chemistry community, soft modeling has been a powerful approach not only for enhancing the accuracy of hard modeling (82) and (83) but also for making fast”