1-Lipschitz layers compared: Memory, speed, and certifiable robustness
B. Prach, F. Brau, G. Buttazzo, C. Lampert, in:, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Computer Vision Foundation, 2024, pp. 24574–24583.

Intriguing properties of robust classification

1-Lipschitz neural networks are more expressive with N-activations
B. Prach, C. Lampert, ArXiv (n.d.).

Almost-orthogonal layers for efficient general-purpose Lipschitz networks
B. Prach, C. Lampert, in:, Computer Vision – ECCV 2022, Springer Nature, 2022, pp. 350–365.