pytorch_gum_uncertainty_propagation
v0.18.0

Getting started:

  • GUM-compliant_neural-network_uncertainty-propagation
    • Getting started
    • Documentation
    • Disclaimer
    • License

Detailed information:

  • Installation
    • Quick setup (not recommended)
      • Updating to the newest version
    • Proper Python setup with virtual environment (recommended)
      • Set up a virtual environment
        • Create a venv Python environment on Windows
        • Create a venv Python environment on Mac & Linux
      • Install pytorch_gum_uncertainty_propagation via pip
      • Optional Jupyter Notebook dependencies
      • Install known to work dependencies’ versions
      • Optional dependencies
  • Changelog
    • v0.18.0 (2023-01-24)
      • Feature
      • Documentation
    • v0.17.1 (2023-01-21)
      • Fix
      • Documentation
    • v0.17.0 (2023-01-20)
      • Feature
    • v0.16.0 (2023-01-20)
      • Feature
      • Documentation
    • v0.15.0 (2023-01-17)
      • Feature
      • Documentation
    • v0.14.0 (2022-12-21)
      • Feature
      • Documentation
    • v0.13.0 (2022-12-21)
      • Feature
      • Documentation
    • v0.12.0 (2022-12-21)
      • Feature
      • Fix
      • Documentation
    • v0.11.0 (2022-12-21)
      • Feature
      • Fix
    • v0.10.0 (2022-12-20)
      • Feature
      • Fix
      • Documentation
      • Performance
    • v0.9.0 (2022-12-17)
      • Feature
    • v0.8.0 (2022-12-17)
      • Feature
      • Documentation
    • v0.7.0 (2022-12-15)
      • Feature
      • Documentation
    • v0.6.0 (2022-12-14)
      • Feature
      • Fix
    • v0.5.0 (2022-12-11)
      • Feature
    • v0.4.0 (2022-12-11)
      • Feature
      • Documentation
    • v0.3.0 (2022-12-10)
      • Feature
      • Documentation
    • v0.2.0 (2022-12-09)
      • Feature
      • Documentation
    • v0.1.0 (2022-12-03)
      • Feature

Examples:

  • Examples
    • Proof-of-Concept examples
      • Script to propagate inputs for several architectures and activations
      • Utility module to construct valid covariance matrices from standard uncertainties
      • Visualizations of activation functions
        • Plot with Plotly
        • Graph of QuadLU
        • Graph of softplus
        • Graph of sigmoid
  • Propagate ZeMA samples through MLPs
  • ZeMA dataset API

Code Reference:

  • Modules
  • Functionals
  • Uncertainties
pytorch_gum_uncertainty_propagation
  • Search

© Copyright 2023, B. Ludwig (PTB). Revision b5163c04.

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