Responsible Model Selection with Virny and VirnyView

Denys Herasymuk, Falaah Arif Khan, Julia Stoyanovich

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    In this demonstration, we present a comprehensive software library for model auditing and responsible model selection, called Virny, along with an interactive tool called VirnyView. Our library is modular and extensible, it implements a rich set of performance and fairness metrics, including novel metrics that quantify and compare model stability and uncertainty, and enables performance analysis based on multiple sensitive attributes, and their intersections. The Virny library and the VirnyView tool are available at and

    Original languageEnglish (US)
    Title of host publicationSIGMOD-Companion 2024 - Companion of the 2024 International Conferaence on Management of Data
    PublisherAssociation for Computing Machinery
    Number of pages4
    ISBN (Electronic)9798400704222
    StatePublished - Jun 9 2024
    Event2024 International Conferaence on Management of Data, SIGMOD 2024 - Santiago, Chile
    Duration: Jun 9 2024Jun 15 2024

    Publication series

    NameProceedings of the ACM SIGMOD International Conference on Management of Data
    ISSN (Print)0730-8078


    Conference2024 International Conferaence on Management of Data, SIGMOD 2024


    • data-centric ai
    • fairness
    • model selection
    • robustness
    • stability

    ASJC Scopus subject areas

    • Software
    • Information Systems


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