Exploring chemical space with discrete, gradient, and hybrid optimization methods.

By D. Balamurugan, Weitao Yang, David N. Beratan. 2008

35 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Electronic, Optical and Magnetic Materials, Materials 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. Benjamín Sánchez-Lengeling
2. Alán Aspuru-Guzik
3. Gabriel Lima Guimaraes
4. Carlos Outeiral
5. Nicholas J. Schork
6. José Miguel Hernández-Lobato
7. Ryan Jacobs
8. Dane Morgan

In Materials Chemistry

1. Benjamín Sánchez-Lengeling
2. Alán Aspuru-Guzik
3. Gabriel Lima Guimaraes
4. José Miguel Hernández-Lobato
5. Nicholas J. Schork
6. Thomas Kipf
7. Ryan Jacobs
8. Dane Morgan

Citations in the corpus

• Optimizing distributions over molecular space. An Objective-Reinforced Generative Adversarial Network for Inverse-design Chemistry (ORGANIC) (2017, background): “Current strategies to explore and discover molecules lie with high-throughput virtual screening [2] or discrete local search methods such as genetic algorithms [3–5].”