Robust quantum dots charge autotuning using neural network uncertainty

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DOIResolve DOI: https://doi.org/10.1088/2632-2153/ad88d5
AuthorSearch for: ORCID identifier: https://orcid.org/0000-0003-4517-5042; Search for: ORCID identifier: https://orcid.org/0009-0005-0384-1109; Search for: ORCID identifier: https://orcid.org/0009-0003-5789-3807; Search for: ; Search for: ORCID identifier: https://orcid.org/0000-0002-5244-3474; Search for: ORCID identifier: https://orcid.org/0000-0002-2145-7590; Search for: ; Search for: ORCID identifier: https://orcid.org/0000-0002-1314-9715; Search for: 1ORCID identifier: https://orcid.org/0000-0002-1929-2715; Search for: ; Search for: ORCID identifier: https://orcid.org/0000-0003-0311-8840; Search for: ORCID identifier: https://orcid.org/0000-0002-5505-8176; Search for: ORCID identifier: https://orcid.org/0000-0003-2156-967X
Affiliation
  1. National Research Council of Canada. Quantum and Nanotechnologies
FunderSearch for: Fonds de Recherche du Québec - Nature et Technologies; Search for: National Science Engineering Research Council of Canada
FormatText, Article
Subjectartificial neural network; Bayesian nerual network; quantum dot; charge autotuning; uncertainty estimation
Abstract
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PublisherIOP Publishing
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LanguageEnglish
Peer reviewedYes
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Record identifieraee92f00-a3f7-4a2d-814e-4a47153aaa1b
Record created2025-04-02
Record modified2025-04-02
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