Past Events

In 1982, Livingston showed that several examples of Seifert surfaces that are not isotopic in the 3-sphere become isotopic when pushed into the 4-ball. This is consistent with a common intuition in topology: objects that are somehow similar should...

The principle of ‘maximum entropy’ states that the probability distribution which best represents the current state of knowledge about a system is the one with largest entropy with respect to a given prior (data) distribution. It was first formulated...

A process Y is a factor of a process X if it can be written as Y=F(X) for some function F which commutes with translations. The factor is finitary if Y_0 is almost surely determined by some finite portion of the input X. Given a process Y, the...

This work describes how machine learning may be used to develop accurate and efficient nonlinear dynamical systems models for complex natural and engineered systems. We explore the sparse identification of nonlinear dynamics (SINDy) algorithm, which...

We compute extreme values of the Riemann Zeta function at the critical points of the zeta function in the critical strip. i.e. the points where ζ′(s)=0 and Rs1. We show that the values taken by the zeta function at these points are very similar to...

We apply and extend the renormalisation group method developed by Bauerschmidt, Brydges and Slade to analyse near-critical finite-size scaling for the 4-dimensional n-component hierarchical |ϕ| 4 model, for all n=1,2,3,… In particular, we compute the...

We propose an extension of the well-known Klausmeier model of vegetation to two plant species that consume water at different rates. Rather than competing directly, the plants compete through their intake of water, which is a shared resource between...

The Non Linear Schrodinger Equation is a canonical example of a dispersive PDE that can also display stable, spatially localized solutions called solitons. Invariant measures for the flow of the equation have been used to study not only the well...

Optimal transportation, at its core, is a powerful framework for obtaining structured yet general couplings between general probability measures based on matching underlying characteristics. This framework lends itself naturally to applications in...