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20152023
most citedTowards Proving the Adversarial Robustness of Deep Neural Networks

119 citations · 468 across the 39 of their papers we have counts for

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8 papers · 1 filter

cs.LO2023

Towards a Certified Proof Checker for Deep Neural Network Verification

Remi Desmartin, Omri Isac, Grant Passmore +3

Recent developments in deep neural networks (DNNs) have led to their adoption in safety-critical systems, which in turn has heightened the need for guaranteeing their safety. These…

cs.LO2023

DelBugV: Delta-Debugging Neural Network Verifiers

Raya Elsaleh, Guy Katz

Deep neural networks (DNNs) are becoming a key component in diverse systems across the board. However, despite their success, they often err miserably; and this has triggered signi…

cs.LO2023

DNN Verification, Reachability, and the Exponential Function Problem

Omri Isac, Yoni Zohar, Clark Barrett +1

Deep neural networks (DNNs) are increasingly being deployed to perform safety-critical tasks. The opacity of DNNs, which prevents humans from reasoning about them, presents new saf…

cs.LO2022

veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System

Guy Amir, Ziv Freund, Guy Katz +2

In this short paper, we present our ongoing work on the veriFIRE project -- a collaboration between industry and academia, aimed at using verification for increasing the reliabilit…

cs.LO2022★ 1 cited

Neural Network Verification with Proof Production

Omri Isac, Clark Barrett, Min Zhang +1

Deep neural networks (DNNs) are increasingly being employed in safety-critical systems, and there is an urgent need to guarantee their correctness. Consequently, the verification c…

cs.LO2020★ 25 cited

Parallelization Techniques for Verifying Neural Networks

Haoze Wu, Alex Ozdemir, Aleksandar Zeljić +7

Inspired by recent successes with parallel optimization techniques for solving Boolean satisfiability, we investigate a set of strategies and heuristics that aim to leverage parall…

cs.LO2019★ 1 cited

Simplifying Neural Networks using Formal Verification

Sumathi Gokulanathan, Alexander Feldsher, Adi Malca +2

Deep neural network (DNN) verification is an emerging field, with diverse verification engines quickly becoming available. Demonstrating the effectiveness of these engines on real-…

cs.LO2016★ 7 cited

Extending SMTCoq, a Certified Checker for SMT (Extended Abstract)

Burak Ekici, Guy Katz, Chantal Keller +3

This extended abstract reports on current progress of SMTCoq, a communication tool between the Coq proof assistant and external SAT and SMT solvers. Based on a checker for generic…