Caltech/USC/UCLA Joint Topology Seminar

TO BE HELD AT UCLA MS 6627

In recent years neural networks have received a great deal of attention due to their remarkable ability to detect subtle and very complex patterns in large data sets. They have become an important machine learning tool and have been used extensively in many fields, including computer vision, fraud detection, artificial intelligence, and financial modeling. Knots in 3-space and their associated invariants provide a rich data set (with many unanswered questions) on which to apply these techniques. In this talk I will describe neural networks, and outline how they can be applied to the study of knots in 3-space. Indeed, these networks can be applied to answer a number of algebraic and geometric problems involving knots and their invariants. I will also outline how neural networks can be used together with techniques from reinforcement learning to construct explicit examples of slice and ribbon surfaces for certain knots.