Robustness to Adversarial Attacks in Learning-Enabled Controllers Xiong, Z., Eappen, J., Zhu, H., & Jagannathan, S. (2020). Robustness to Adversarial Attacks in Learning-Enabled Controllers. ArXiv E-Prints, arXiv:2006.06861. (Original work published 2025)
GPU Accelerated Sub-Sampled Newton's Method Kylasa, S., Roosta-Khorasani, F., Mahoney, M., & Grama, A. (2018). GPU Accelerated Sub-Sampled Newton’s Method. ArXiv E-Prints, arXiv:1802.09113. (Original work published 2025)
Simplifying Neural Networks using Formal Verification Gokulanathan, S., Feldsher, A., Malca, A., Barrett, C., & Katz, G. (2019). Simplifying Neural Networks using Formal Verification. ArXiv E-Prints, arXiv:1910.12396. (Original work published 2025)
An SMT-Based Approach for Verifying Binarized Neural Networks Amir, G., Wu, H., Barrett, C., & Katz, G. (2020). An SMT-Based Approach for Verifying Binarized Neural Networks. ArXiv E-Prints, arXiv:2011.02948.
Parallelization Techniques for Verifying Neural Networks Wu, H., Ozdemir, A., c, A., Irfan, A., Julian, K., Gopinath, D., … Barrett, C. (2020). Parallelization Techniques for Verifying Neural Networks. ArXiv E-Prints, arXiv:2004.08440. (Original work published 2025)