SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Published: Jun 26, 2017
Abstract
Deep learning has the potential to revolutionize quantum chemistry as it is ideally suited to learn representations for structured data and speed up the exploration of chemical space. While convolutional neural networks have proven to be the first choice for images, audio and video data, the atoms in molecules are not restricted to a grid. Instead, their precise locations contain essential physical information, that would get lost if...
Paper Details
Title
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Published Date
Jun 26, 2017
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