1. Albarghouthi, A.: Introduction to Neural Network Verification (2021)
2. Athalye, A., Carlini, N., Wagner, D.: Obfuscated gradients give a false sense of security: circumventing defenses to adversarial examples (2018)
3. Calin, O.: Deep Learning Architectures - A Mathematical Approach. Springer, Heidelberg (2020). https://doi.org/10.1007/978-3-030-36721-3
4. Carlini, N., Liu, C., Erlingsson, Ú., Kos, J., Song, D.: The secret sharer: evaluating and testing unintended memorization in neural networks (2019)
5. Casadio, M., Komendantskaya, E., Daggitt, M.L., Kokke, W., Katz, G., Amir, G., Refaeli, I.: Neural network robustness as a verification property: a principled case study (2021)