Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. - Guy Katz; Clark W. Barrett; David L. Dill; Kyle Julian; Mykel J. Kochenderfer (CAV (1), 2017)

Towards Proving the Adversarial Robustness of Deep Neural Networks. - Guy Katz; Clark W. Barrett; David L. Dill; Kyle Julian; Mykel J. Kochenderfer (FVAV@iFM, 2017)

Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty. - Maxime Bouton; Kyle Julian; Alireza Nakhaei; Kikuo Fujimura; Mykel J. Kochenderfer (AAMAS, 2018)

Toward Scalable Verification for Safety-Critical Deep Networks. - Lindsey Kuper; Guy Katz; Justin Gottschlich; Kyle Julian; Clark W. Barrett; Mykel J. Kochenderfer (CoRR, 2018)

Image-based Guidance of Autonomous Aircraft for Wildfire Surveillance and Prediction. - Kyle D. Julian; Mykel J. Kochenderfer (CoRR, 2018)

Deep Neural Network Compression for Aircraft Collision Avoidance Systems. - Kyle D. Julian; Mykel J. Kochenderfer; Michael P. Owen (CoRR, 2018)

Distributed Wildfire Surveillance with Autonomous Aircraft using Deep Reinforcement Learning. - Kyle D. Julian; Mykel J. Kochenderfer (CoRR, 2018)

Visual Depth Mapping from Monocular Images using Recurrent Convolutional Neural Networks. - John Mern; Kyle Julian; Rachael E. Tompa; Mykel J. Kochenderfer (CoRR, 2018)

The Marabou Framework for Verification and Analysis of Deep Neural Networks. - Guy Katz; Derek A. Huang; Duligur Ibeling; Kyle Julian; Christopher Lazarus; Rachel Lim; Parth Shah 003; Shantanu Thakoor; Haoze Wu 001; Aleksandar Zeljic; David L. Dill; Mykel J. Kochenderfer; et al. (CAV (1), 2019)

Decomposition methods with deep corrections for reinforcement learning. - Maxime Bouton; Kyle D. Julian; Alireza Nakhaei; Kikuo Fujimura; Mykel J. Kochenderfer (Auton. Agents Multi Agent Syst., 2019)

A Reachability Method for Verifying Dynamical Systems with Deep Neural Network Controllers. - Kyle D. Julian; Mykel J. Kochenderfer (CoRR, 2019)

Verifying Aircraft Collision Avoidance Neural Networks Through Linear Approximations of Safe Regions. - Kyle D. Julian; Shivam Sharma; Jean-Baptiste Jeannin; Mykel J. Kochenderfer (CoRR, 2019)

Guaranteeing Safety for Neural Network-Based Aircraft Collision Avoidance Systems. - Kyle D. Julian; Mykel J. Kochenderfer (CoRR, 2019)

Parallelization Techniques for Verifying Neural Networks. - Haoze Wu 001; Alex Ozdemir; Aleksandar Zeljic; Kyle Julian; Ahmed Irfan; Divya Gopinath; Sadjad Fouladi; Guy Katz; Corina S. Pasareanu; Clark W. Barrett (FMCAD, 2020)

Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing. - Kyle D. Julian; Ritchie Lee; Mykel J. Kochenderfer (ITSC, 2020)

Reluplex: a calculus for reasoning about deep neural networks. - Guy Katz; Clark W. Barrett; David L. Dill; Kyle Julian; Mykel J. Kochenderfer (Formal Methods Syst. Des., 2022)

Generating probabilistic safety guarantees for neural network controllers. - Sydney M. Katz; Kyle D. Julian; Christopher A. Strong; Mykel J. Kochenderfer (Mach. Learn., 2023)

Global optimization of objective functions represented by ReLU networks. - Christopher A. Strong; Haoze Wu 001; Aleksandar Zeljic; Kyle D. Julian; Guy Katz; Clark W. Barrett; Mykel J. Kochenderfer (Mach. Learn., 2023)

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. - Haoze Wu 001; Omri Isac; Aleksandar Zeljic; Teruhiro Tagomori; Matthew L. Daggitt; Wen Kokke; Idan Refaeli; Guy Amir; Kyle Julian; Shahaf Bassan; Pei Huang 002; Ori Lahav 002; et al. (CAV (2), 2024)