Information Flow in Deep Neural Networks

Understand

Although deep neural networks have been immensely successful, there is no comprehensive theoretical understanding of how they work or are structured.

• As a result, deep networks are often seen as black boxes with unclear interpretations and reliability.
• Understanding the performance of deep neural networks is one of the greatest scientific challenges.
• This work aims to apply principles and techniques from information theory to deep learning models to increase our theoretical understanding and design better algorithms.