Verifying Properties of Binarized Deep Neural Networks

Understand

Understanding properties of deep neural networks is an important challenge in deep learning.

• In this paper, we take a step in this direction by proposing a rigorous way of verifying properties of a popular class of neural networks, Binarized Neural Networks, using the well-developed means of Boolean satisfiability.
• Our main contribution is a construction that creates a representation of a binarized neural network as a Boolean formula.
• Our encoding is the first exact Boolean representation of a deep neural network.