Simplifying Neural Networks with the Marabou Verification Engine

Deep neural network (DNN) verification is an emerging field, with diverse verification engines quickly becoming available. Demonstrating the effectiveness of these tools on real-world DNNs is an important step towards their wider adoption. We focus here on the recently proposed Marabou verification tool, and demonstrate its usage for a novel application: simplifying neural networks, by reducing the size of a DNN without harming its accuracy. We report on the work-flow of the simplification process, and on its potential significance and applicability to domains of interest.