Dataset Open Access
Martinetto, Vincent; Shah, Karan; Cangi, Attila; Pribram-Jones, Aurora
{ "id": "2720", "DOI": "10.14278/rodare.2720", "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>", "title": "Inverting the Kohn-Sham equations with physics-informed machine learning", "issued": { "date-parts": [ [ 2024, 2, 1 ] ] }, "author": [ { "family": "Martinetto, Vincent" }, { "family": "Shah, Karan" }, { "family": "Cangi, Attila" }, { "family": "Pribram-Jones, Aurora" } ], "type": "dataset", "publisher": "Rodare" }
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Data volume | 2.2 GB | 2.2 GB |
Unique views | 151 | 151 |
Unique downloads | 11 | 11 |