Architecture-Preserving Provable Repair of Deep Neural Networks

Understand

Deep neural networks (DNNs) are becoming increasingly important components of software, and are considered the state-of-the-art solution for a number of problems, such as image recognition.

• However, DNNs are far from infallible, and incorrect behavior of DNNs can have disastrous real-world consequences.
• This paper addresses the problem of architecture-preserving V-polytope provable repair of DNNs.
• A V-polytope defines a convex bounded polytope using its vertex representation.