Deep neural networks are
fragile and their behaviors are often surprising. In many settings, we need to provide formal guarantees on the
safety, security, correctness, or robustness of neural networks. This course covers foundational ideas from
formal verification and their application to deep learning.
The couse is based on chapters from the instructor's ongoing book on the subject and research papers from machine learning and verification.