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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 " GUMcompliant neuralnetwork robustness verification".
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MetHyInfra / HydrogenRealGasModel
GNU General Public License v3.0 or laterUpdated 
ptb843 / Tutorials
GNU General Public License v2.0 or laterUpdated 
ptb843 / QUNOM23 inverse problems tutorial
GNU General Public License v2.0 or laterUpdated 
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ludwig10_masters_thesis / GUMcompliant neural network robustness verification  a Masters thesis
European Union Public License 1.2Updated 
This package accompanies my Master's thesis on GUMcompliant neural network robustness verification and provides an implementation using PySCIPOpt.
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M4D / zema_emc_annotated
MIT LicenseThis codebase provides convenient access to the annotated data set of one electromechanical cylinder at ZeMA testbed.
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ptb843 / neural_networks_101
GNU General Public License v3.0 or laterUpdated 
A simple extension to deep ensembles for an improved uncertainty quantification
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MFM2 / LiquidLevelExtractionUnet
MIT LicenseIn this repository, a Deeplearning model is given, which was trained to extract the vertical position of the gasliquidinterface over time (liquid level time series) from video recordings of horizontal gasliquid pipe flow experiments.
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This project contains the implementation and examples of the publication MM/GW, CE, "A rejection Sampler extending GUMS1", Metrologia, 2021 [TODO].
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Slides from the talk about Data Analysis Using Modern Python
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