Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes

1 code implementation • 28 Jun 2020 • Ryan-Rhys Griffiths, Jake L. Greenfield, Aditya R. Thawani, Arian R. Jamasb, Henry B. Moss, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander A. Aldrick, Matthew J. Fuchter Alpha A. Lee

Separating the electronic absorption bands of these isomers is key to selectively addressing a specific isomer and achieving high photostationary states whilst overall red-shifting the absorption bands serves to limit material damage due to UV-exposure and increases penetration depth in photopharmacological applications.

BIG-bench Machine Learning Gaussian Processes