2021
Scaling Symbolic Methods using Gradients for Neural Model Explanation
ICLR 2021poster
Symbolic techniques based on Satisfiability Modulo Theory (SMT) solvers have been proposed for analyzing and verifying neural network properties, but their usage has been fairly limited owing to their poor scalability with larger networks. In this work, we propose a technique for combining gradient-…