Professor Rebecca Willett (University of Chicago) - The role of depth in neural networks: function space geometry and learnability
Rebecca Willett is a Professor of Statistics and Computer Science & the Faculty Director of AI at the Data Science Institute at Chicago. Her research is focused on machine learning foundations, scientific machine learning, and signal processing.
National PDE Network Meeting: Nonlinear PDEs of Mixed Type in Geometry and Mechanics /Joint with the 13th Oxbridge PDE Conference
Theme: Analysis of nonlinear PDEs of mixed-type (esp. elliptic-hyperbolic and hyperbolic-parabolic mixed PDEs) and related topics
Time & place: 18-22 March 2024 at the Mathematical Institute, University of Oxford
On Saturday 17th February, the Mathematrix and Mirzakhani societies held their inaugural joint conference. There were over 100 attendees from across the UK. The theme of the day was ‘Beyond the Pipeline’ and focused on the issues behind the metaphor of the leaky pipeline and the ways that we can prevent women and other gender minorities from leaving mathematics.
Sarah Livermore (Department for Business and Trade)
Sarah Livermore has worked in the Civil Service for over 10 years, using the maths skills gained in her physics degrees (MPhys, DPhil) whilst studying at Oxford. In this session she’ll discuss some of the roles available to people with a STEM background in the Civil Service, a ‘day in the life’ of a civil servant, typical career paths and how to apply.
Starring Naomi Andrew, Jane Coons, Antonio Esposito, and Romain Ruzziconi
Conferences and networking are important parts of academic life, particularly early in your academic career. But how do you make the most out of conferences? And what are the does and don'ts of networking? Learn about the answers to these questions and more in this panel discussion with postdocs from across the Mathematical Institute.
L1, 4pm today
During the pandemic, you may have seen graphs of data plotted on strange-looking (logarithmic) scales. Oliver will explain some of the basics and history of logarithms, and show why they are a natural tool to represent numbers ranging from COVID data to Instagram followers. In fact, we’ll see how logarithms can even help us understand information itself in a mathematical way.
