Dataset Open Access
Martinetto, Vincent;
Shah, Karan;
Cangi, Attila;
Pribram-Jones, Aurora
{ "issued": { "date-parts": [ [ 2024, 2, 1 ] ] }, "author": [ { "family": "Martinetto, Vincent" }, { "family": "Shah, Karan" }, { "family": "Cangi, Attila" }, { "family": "Pribram-Jones, Aurora" } ], "id": "2720", "DOI": "10.14278/rodare.2720", "publisher": "Rodare", "abstract": "<p>This data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning". </p>\n\n<p>It contains the data generation scripts, datasets for the systems used in the paper (Single Well - 1D atom, Double Well - 1D diatomic molecule) and output potentials generated by the physics-informed machine learning models (physics-informed neural networks and Fourier neural operators).</p>", "type": "dataset", "title": "Inverting the Kohn-Sham equations with physics-informed machine learning" }
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