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A simple extension to deep ensembles for an improved uncertainty quantification
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DigitalDynamicMeasurement / Bokeh CSS PTB
GNU Lesser General Public License v2.1 onlyUpdated -
Conditioning, processing and preparation of bureaucracy related database requests.
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Conditioning, processing and preparation of calibration document related database requests.
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M4D / Cocalibration Demonstrator Backend
MIT LicenseUpdated -
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DigitalDynamicMeasurement / dccQuantities
GNU Lesser General Public License v2.1 onlyPython classes for working with DDC calibration data
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DigitalDynamicMeasurement / dccXMLJSONConv
GNU Lesser General Public License v2.1 onlyUpdated -
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DigitalDynamicMeasurement / DSI Parser Frontend
GNU Lesser General Public License v2.1 onlyUpdated -
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This code base is intended to serve as a starting point for interested researchers or practitioners to extend or apply the uncertainty propagation portion of the author's Master's thesis " GUM-compliant neural-network robustness verification".
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This project contains the implementation and examples of the publication MM/GW, CE, "A rejection Sampler extending GUM-S1", Metrologia, 2021 [TODO].
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