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pytorch_gum_uncertainty_propagation

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 17 Jan 2023Publisher:Zenodo
Authors: Ludwig, Björn;
Code repository: https://github.com/BjoernLudwigPTB/pytorch_gum_uncertainty_propagation/tree/v0.17.1

doi: 10.5281/zenodo.7557324 , 10.5281/zenodo.7566683 , 10.5281/zenodo.7554500 , 10.5281/zenodo.7552896 , 10.5281/zenodo.7552895

pytorch_gum_uncertainty_propagation

Abstract

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". It provides an implementation using pytorch for Python 3.10.

If you use this software, please cite it using the provided metadata.

Related Organizations
Keywords

GUM, pytorch, measurement uncertainties, uncertainty propagation, neural networks

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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