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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
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations—0
EL-MLFFs: Ensemble Learning of Machine Leaning Force Fields—0
Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials—0
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems—0
ForceNet: A Graph Neural Network for Large-Scale Quantum Chemistry Simulation—0
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations—0
Graph-Convolutional Deep Learning to Identify Optimized Molecular Configurations—0
A Heterogeneous Parallel Non-von Neumann Architecture System for Accurate and Efficient Machine Learning Molecular Dynamics—0
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