119 citations · 468 across the 39 of their papers we have counts for
4 papers · 1 filter
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks
Divya Gopinath, Guy Katz, Corina S. Pasareanu +1
Deep neural networks have become widely used, obtaining remarkable results in domains such as computer vision, speech recognition, natural language processing, audio recognition, s…
Towards Proving the Adversarial Robustness of Deep Neural Networks
Guy Katz, Clark Barrett, David L. Dill +2
Autonomous vehicles are highly complex systems, required to function reliably in a wide variety of situations. Manually crafting software controllers for these vehicles is difficul…
Provably Minimally-Distorted Adversarial Examples
Nicholas Carlini, Guy Katz, Clark Barrett +1
The ability to deploy neural networks in real-world, safety-critical systems is severely limited by the presence of adversarial examples: slightly perturbed inputs that are misclas…
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz, Clark Barrett, David Dill +2
Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical syst…