zonolayer 0.4.0

Last-layer uncertainty modeling via zonotopic representations.

Zonolayer

Matthew McCann
University of Strathclyde, 2025

Developed with guidance and support from Marco de Angelis, University of Strathclyde

Zonolayer is a Python package for last-layer uncertainty modeling via zonotopic representations.
It provides zonotopic output bounds and statistical prediction intervals for neural networks with interval-bounded outputs, enabling precise and interpretable uncertainty quantification in regression tasks.

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Features

• Compute zonotopic bounds for last-layer outputs.
• Combine statistical prediction intervals with interval uncertainty.
• Compatible with PyTorch networks exposing latent features.
• Modular, research-friendly, and easy to use.

By default, Zonolayer relies on NumPy for all numerical computations and interval handling.

If you require more advanced interval arithmetic (e.g., using pyinterval or other specialized packages), you can install the optional dependencies and modify the code accordingly, or submit a request for support to be added. I appreciate any and all feedback.

IPM support using the PyIPM library by J. Sadeghi

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Installation

Ensure all requirements from requirements.txt are installed to reduce any potential issues.

pip install zonolayer

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Getting Started

See basic_usage.py in the examples directory for the quickest method to get up and running and start experimenting with the library.

Example Plots

Zonolayer produces zonotopic bounds and statistical prediction intervals. Example outputs: