PCTS Seminar Series: Deep Learning for Physics

“Deep learning” refers to use of neural networks to solve learning problems, including “learning” hidden structures in large and complex data sets. The theory for this field is still in its infancy. Lately physical and biological scientists have begun to explore how it might apply to their domains. This seminar series seeks to introduce the theoretical science community in Princeton and surrounding regions to the practice, promise, and problems of deep learning. It will consist of monthly afternoon sessions ---geared to the broader scientific community--- that will feature an invited talk followed by informal discussions among participants. The schedule will be updated whenever dates for new speakers are confirmed.