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20132026
most citedANI-1: An extensible neural network potential with DFT accuracy at force field computational cost

2.1k citations · 3.9k across the 15 of their papers we have counts for

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Showing 2017Show all

2 papers · 1 filter

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.chem-ph2017★ 341 cited

ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules

Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg

One of the grand challenges in modern theoretical chemistry is designing and implementing approximations that expedite ab initio methods without loss of accuracy. Machine learning…