Verified Deep Learning

A book by Aws Albarghouthi

Deep learning has transformed the way we think of software and what it can do. But 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 in-progress book covers foundational ideas from formal verification and their application to reasoning about deep learning.

You can get all available chapters as one pdf or access individual chapters below. Keep in mind that the book is constantly evolving.

About this book

I Neural networks and correctness

II Constraint-based verification

III Abstraction-based verification

IV Verification and reinforcement learning

For comments, contact the author.
Please use the following to cite this book.
    title = {Verified Deep Learning},
    author = {Aws Albarghouthi},
    publisher = {},
    note = {\url{}},
    year = {2020}
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