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Atomic Forces

Predicion of the atomic forces, generally calculated with a quantum mechanical code (e.g. at DFT theory).

Papers

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Showing 21–28 of 28 papers

TitleStatusHype
Graph-Convolutional Deep Learning to Identify Optimized Molecular Configurations—0
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations—0
ForceNet: A Graph Neural Network for Large-Scale Quantum Chemistry Simulation—0
Simple and efficient algorithms for training machine learning potentials to force data—0
sGDML: Constructing Accurate and Data Efficient Molecular Force Fields Using Machine LearningCode0
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems—0
Nudged elastic band calculations accelerated with Gaussian process regression—0
Machine Learning of Accurate Energy-conserving Molecular Force FieldsCode0
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