Verification of Neural Networks (Lecture Notes)
arXiv:2604.2573310.1
AI Analysis
Provides a theoretical introduction to neural network verification for researchers and students, but is incremental as it synthesizes existing knowledge.
These lecture notes introduce neural network verification from a theoretical perspective, covering feed-forward, recurrent, attention, and transformer architectures along with specification languages and algorithmic verification techniques.
These lecture notes provide an introduction to the verification of neural networks from a theoretical perspective. We discuss feed-forward neural networks, recurrent neural networks, attention mechanisms, and transformers, together with specification languages and algorithmic verification techniques.