Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that
arise in quantum physics and random matrix theory. In contrast to traditional structured …

The increasing availability of both interesting data and processing capacity has led to
widespread interest in machine learning techniques that deal with complex, structured …

On an annulus A q:={z∈ C: q<| z|< 1} with a fixed q∈(0, 1), we study a Gaussian analytic
function (GAF) and its zero set which defines a point process on A q called the zero point …

Cayley's first hyperdeterminant is a straightforward generalization of determinants for
tensors. We prove that nonzero hyperdeterminants imply lower bounds on some types of …

For a given positive integer $ m $, the concept of {\it hyperdeterminantal total positivity} is
defined for a kernel $ K:\R^{2m}\to\R $, thereby generalizing the classical concept of total …

Symanzik polynomials are defined on Feynman graphs and they are used in quantum field
theory to compute Feynman amplitudes. They also appear in mathematics from different …

In this thesis, we prove that the tropical cohomology of a smooth projective tropical variety
verifies several symmetry properties: namely, tropical analogs of the Kähler package …

We use techniques in the shuffle algebra to present a formula for the partition function of a
one-dimensional log-gas comprised of particles of (possibly) different integer charges at …

We use techniques in the shuffle and exterior algebras to present the partition functions for
several log-gas models in terms of either the Hyperpfaffian or the Berezin integral of an …

Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that
arise in quantum physics and random matrix theory. In contrast to traditional structured …