PHY 8000 Seminar: "Theoretical Perspectives on Deep Learning"

The Physics seminar speaker this week will be Dr. Nati Swebro of the Toyota Technological Institute at Chicago (pre-recorded). The talk was originally presented at the 2019 National Academy of Sciences Sackler Symposium on “The Science of Deep Learning."  

The talk is titled "Theoretical Perspectives on Deep Learning."

The symposium vision follows:

Artificial neural networks have re-emerged as a powerful concept for designing state-of-the-art algorithms in machine learning and artificial intelligence. Across a variety of fields, these architectures seem to outperform time-honored machine learning methods. Interestingly, our understanding of why and when these methods work remains limited. At the same time, an increasing number of mission-critical systems depend on deep neural networks, from autonomous vehicles to social media platforms that influence political discourse. Scientists are also beginning to rely more on deep learning as a knowledge discovery tool as research becomes ever more data driven.