Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra

Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra

Abstract Deep learning methods for the prediction of molecular excitation spectra are presented. For the example of the electronic density of states of 132k organic molecules, three different neural network architectures: multilayer perceptron (MLP), convolutional neural network (CNN), and deep tens...

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Bibliographic Details
Main Authors: Kunal Ghosh, Annika Stuke, Milica Todorović, Peter Bjørn Jørgensen, Mikkel N. Schmidt, Aki Vehtari, Patrick Rinke
Format: Article
Language:English
Published: Wiley 2019-05-01
Series:Advanced Science
Subjects:
artificial intelligence
DFT calculations
excitation spectra
neural networks
organic molecules
Online Access:https://doi.org/10.1002/advs.201801367

Internet

https://doi.org/10.1002/advs.201801367

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