Machine Learning Configuration Interaction
Published in arXiv (Cornell University) • Aug 17, 2018
NobleIDNI7P78W43R44S65
Authors:
J. P. Coe
Abstract
We propose the concept of machine learning configuration interaction (MLCI) whereby an artificial neural network is trained on-the-fly to predict important new configurations in an iterative selected configuration interaction procedure. We demonstrate that the neural network can discriminate between...
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