BoundLab Documentation#
BoundLab is a framework for building neural network verification tools using symbolic expressions and bound propagation.
Mental model: represent relaxed abstract values as Expr, transform them (for example with zono.interpret), then apply dual-norm concretization (ub, lb, ublb).
This documentation is organized into three learning paths:
Getting Started: install BoundLab and run your first bound computation.User Guide: understand the expression system, propagation APIs, and interpreter workflow.Examples: end-to-end patterns you can adapt to your own models.
Install BoundLab and run your first verification script.
Core concepts, supported operations, and practical workflow guidance.
Task-focused examples from manual expression building to model interpretation.
Autogenerated API docs for all public modules, classes, and functions.