872 citations · 2.9k across the 35 of their papers we have counts for
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stat.ML2017★ 309 cited
Hierarchical modeling of molecular energies using a deep neural network
Nicholas Lubbers, Justin S. Smith, Kipton Barros
We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion,…
physics.geo-ph2017★ 434 cited
Machine Learning Predicts Laboratory Earthquakes
Bertrand Rouet-Leduc, Claudia Hulbert, Nicholas Lubbers +3
Forecasting fault failure is a fundamental but elusive goal in earthquake science. Here we show that by listening to the acoustic signal emitted by a laboratory fault, machine lear…