April 21, 2024 In Unkategorisiert
World geometry of chemical graph neural community representations on the subject of chemical moieties
Digital Discovery, 2024, Advance Article
DOI: 10.1039/D3DD00200D, Paper
DOI: 10.1039/D3DD00200D, Paper
Open Access
  This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Amer Marwan El-Samman, Incé Amina Husain, Mai Huynh, Stefano De Castro, Brooke Morton, Stijn De Baerdemacker
The embedding vectors from a Graph Neural Network trained on quantum chemical data allow for a global geometric space with a Euclidean distance metric. Moieties that are close in chemical sense, are also close in Euclidean sense.
To cite this article before page numbers are assigned, use the DOI form of citation above.
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The embedding vectors from a Graph Neural Network trained on quantum chemical data allow for a global geometric space with a Euclidean distance metric. Moieties that are close in chemical sense, are also close in Euclidean sense.
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry
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