119 citations · 120 across the 2 of their papers we have counts for
11 papers
Generating Probabilistic Safety Guarantees for Neural Network Controllers
Sydney M. Katz, Kyle D. Julian, Christopher A. Strong +1
Neural networks serve as effective controllers in a variety of complex settings due to their ability to represent expressive policies. The complex nature of neural networks, howeve…
Global Optimization of Objective Functions Represented by ReLU Networks
Christopher A. Strong, Haoze Wu, Aleksandar Zeljić +4
Neural networks can learn complex, non-convex functions, and it is challenging to guarantee their correct behavior in safety-critical contexts. Many approaches exist to find failur…
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…
Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing
Kyle D. Julian, Ritchie Lee, Mykel J. Kochenderfer
Neural networks have become state-of-the-art for computer vision problems because of their ability to efficiently model complex functions from large amounts of data. While neural n…
Guaranteeing Safety for Neural Network-Based Aircraft Collision Avoidance Systems
Kyle D. Julian, Mykel J. Kochenderfer
The decision logic for the ACAS X family of aircraft collision avoidance systems is represented as a large numeric table. Due to storage constraints of certified avionics hardware,…
Distributed Wildfire Surveillance with Autonomous Aircraft using Deep Reinforcement Learning
Kyle D. Julian, Mykel J. Kochenderfer
Teams of autonomous unmanned aircraft can be used to monitor wildfires, enabling firefighters to make informed decisions. However, controlling multiple autonomous fixed-wing aircra…