3 citations · 3 across the 2 of their papers we have counts for
4 papers
A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks
Christopher Lazarus, Mykel J. Kochenderfer
Many approaches for verifying input-output properties of neural networks have been proposed recently. However, existing algorithms do not scale well to large networks. Recent work…
Deep Binary Reinforcement Learning for Scalable Verification
Christopher Lazarus, Mykel J. Kochenderfer
The use of neural networks as function approximators has enabled many advances in reinforcement learning (RL). The generalization power of neural networks combined with advances in…
Runtime Safety Assurance Using Reinforcement Learning
Christopher Lazarus, James G. Lopez, Mykel J. Kochenderfer
The airworthiness and safety of a non-pedigreed autopilot must be verified, but the cost to formally do so can be prohibitive. We can bypass formal verification of non-pedigreed co…
Algorithms for Verifying Deep Neural Networks
Changliu Liu, Tomer Arnon, Christopher Lazarus +3
Deep neural networks are widely used for nonlinear function approximation with applications ranging from computer vision to control. Although these networks involve the composition…