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GPT-4 as an interface between researchers and computational software: improving usability and reproducibility
We focus on a widely used software for molecular dynamics simulations, the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), and quantify the usefulness of input files generated by GPT-4 from task descriptions in English and its ability to generate detailed descriptions of computational tasks from input files.
Parsimonious neural networks learn interpretable physical laws
Machine learning is playing an increasing role in the physical sciences and significant progress has been made towards embedding domain knowledge into models.
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