The Principles of Deep Learning Theory
This textbook establishes a theoretical framework for understanding deep learning
models of practical relevance. With an approach that borrows from theoretical
physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic
deep neural networks actually work. To make results from the theoretical forefront
accessible, the authors eschew the subject’s traditional emphasis on intimidating
formality without sacrificing accuracy. Straightforward and approachable, this volume
balances detailed first-principle derivations of novel results with insight and intuition
for theorists and practitioners alike. This self-contained textbook is ideal for students
and researchers interested in artificial intelligence with minimal prerequisites of linear
algebra, calculus, and informal probability theory, and it can easily fill a semester-long
course on deep learning theory. For the first time, the exciting practical advances
in modern artificial intelligence capabilities can be matched with a set of effective
principles, providing a timeless blueprint for theoretical research in deep learning.
Daniel A. Robertswas cofounder and CTO of Diffeo, an AI company acquired by
Salesforce; a research scientist at Facebook AI Research; and a member of the School
of Natural Sciences at the Institute for Advanced Study in Princeton, NJ. He was a
Hertz Fellow, earning a PhD from MIT in theoretical physics, and was also a Marshall
Scholar at Cambridge and Oxford Universities.
Sho Yaidais a research scientist at Meta AI. Prior to joining Meta AI, he obtained
his PhD in physics at Stanford University and held postdoctoral positions at MIT and
at Duke University. At Meta AI, he uses tools from theoretical physics to understand
neural networks, the topic of this book.
Boris Haninis an assistant professor at Princeton University in the Operations
Research and Financial Engineering Department. Prior to joining Princeton in 2020,
Boris was an assistant
The Principles of Deep Learning Theory_Daniel A. Roberts, Sho Yaida, Boris Hanin.pdf