arXiv Machine Learning July 21, 2026 By R\'ois\'in Luo, James McDermott, Colm O'Riordan

Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness

Read the original on arXiv Machine Learning →

arXiv:2607. 16329v1 Announce Type: cross Abstract: Lipschitz continuity is a fundamental property of neural networks that characterizes their sensitivity to input perturbations.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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