Past Events

We study a simple SIS epidemic model accounting for human behaviour. Individuals can decide at each instant of time whether or not they adopt prophylactic (hereafter protection) measures such as mask wearing or social distancing. These measures...

Matroids are combinatorial objects that abstract the notion of independence. The motivating examples are matroids arising from vector configurations. An important tool for studying matroids is the associated Chow ring. A recent result of Adiprasito...

A well-known conjecture in physical literature states that high frequency waves propagating over long distances through turbulence eventually become complex Gaussian distributed. The intensity of such wave fields then follows an exponential law...

For a number field K, the P\'olya group of K, denoted by Po(K), is the subgroup of the ideal class group of K generated by the classes of the products of maximal ideals of K with the same norm. In this talk, after reviewing some results concerning Po...

The practical performance of an optimization method depends on details such as using good step sizes. Strategies for setting step sizes are generally limited to hyperparameter tuning (for a fixed step size), step size schedules and line searches. For...

In defining colouring of oriented graphs via homomorphism one finds an easily checkable necessary condition for a valid colouring — vertices at directed distance at most two must receive different colours. With this idea in mind we extend the...

We prove a new signed elementary symmetric function expansion of the chromatic symmetric function. We then use sign-reversing involutions to prove e -positivity for graphs formed by joining cycles or cliques at single vertices. By considering...

In this talk we will discuss the behaviour of the Riemann zeta on the critical line, and in particular, its correlations in various ranges. We will prove a new result for correlations of squares, where shifts may be up to size T3/2-ε. We will also...

Operator learning is an emerging field at the intersection of machine learning, physics, and mathematics, that aims to discover properties of unknown physical systems from experimental data. Popular techniques exploit the approximation power of deep...

In 1973, assuming the Riemann hypothesis (RH), Montgomery studied the vertical distribution of zeta zeros, and conjectured that they behave like the eigenvalues of some random matrices. We will discuss some models for zeta zeros - starting from the...