When Terry Tao speaks the mathematical world listens.
Last month Terry gave the Oxford Mathematics London Public Lecture at the Science Museum, revealing his thoughts on the potential of Artificial Intelligence for science and mathematics before joining fellow mathematician Po-Shen Lo for a fireside chat.
What does he think? Well, he certainly sees a future where mathematics is embracing and benefiting from AI. It might even bring more mathematicians in to the subject, some of them not even professionals.
Machine learning in solution of inverse problems: subjective perspective
Abstract
Following the 2012 breakthrough in deep learning for classification and visions problems, the last decade has seen tremendous raise of interest in machine learning in a wider mathematical research community from foundational research through field specific analysis to applications.
As data is at the core of any inverse problem, it was a natural direction for the field to investigate how machine learning could aid various aspects of inversion yielding numerous approaches from somewhat ad-hoc but very effective like learned unrolled methods to provably convergent learned regularisers with everything in between. In this talk I will review some on these developments through a lens of the research of our group.