mlsanityData to 14 Oct 2026

PANNA 2.0: Efficient neural network interatomic potentials and new architectures

arXiv 2305.11805 ↗First posted 19 May 2023physics.comp-ph cond-mat.mtrl-sci cs.LGcited by 1

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Abstract (arXiv)

We present the latest release of PANNA 2.0 (Properties from Artificial Neural Network Architectures), a code for the generation of neural network interatomic potentials based on local atomic descriptors and multilayer perceptrons. Built on a new back end, this new release of PANNA features improved tools for customizing and monitoring network training, better GPU support including a fast descriptor calculator, new plugins for external codes and a new architecture for the inclusion of long-range electrostatic interactions through a variational charge equilibration scheme. We present an overview of the main features of the new code, and several benchmarks comparing the accuracy of PANNA models to the state of the art, on commonly used benchmarks as well as richer datasets.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 57 references that are in the map. First posted on arXiv 19 May 2023.

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14 of 57 references.

References · 14

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2 more
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  1. 2025Compact Artificial Neural Network Models for Predicting Protein Residue -- RNA Base Bindingcited by 0