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Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification

Michael Weiss; Paolo Tonella

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    <subfield code="a">&lt;p&gt;Uncertainty and confidence have been shown to be useful metrics in a wide variety of techniques proposed for deep learning testing, including test data selection and system supervision.&amp;nbsp;We present Uncertainty-Wizard, a tool that allows to quantify such uncertainty and confidence in&amp;nbsp; artificial neural networks.&amp;nbsp;It is built on top of the industry-leading tf.keras deep learning API and it provides a near-transparent and&amp;nbsp; easy to understand interface.&amp;nbsp;At the same time, it includes major performance optimizations that we benchmarked on two different machines and different configurations.&lt;/p&gt;</subfield>
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