1 citations · 1 across the 1 of their papers we have counts for
2 papers
eess.IV2019★ 1 cited
A Molecular-MNIST Dataset for Machine Learning Study on Diffraction Imaging and Microscopy
Yan Zhang, Steve Farrell, Michael Crowley +2
An image dataset of 10 different size molecules, where each molecule has 2,000 structural variants, is generated from the 2D cross-sectional projection of Molecular Dynamics trajec…
physics.comp-ph2018
Message-passing neural networks for high-throughput polymer screening
Peter C. St. John, Caleb Phillips, Travis W. Kemper +4
Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data machine learning approaches can enable rapid high-throughput virt…