The mini-workshop brought together researchers from hyperbolic geometry and stochastic geometry with the aim of advancing the emerging field of hyperbolic stochastic geometry. It focused on understanding how negative ...

Artificial neural networks (ANNs) have emerged as a powerful tool in modern machine learning, yet their mathematical foundations remain only partially understood. A key challenge is the inherently stochastic nature of ANN ...

In recent decades, renormalisation, which has long been a workman's tool for theoretical physicists, has also become an essential mathematical tool that appears in many guises. Within mathematics, renormalisation bridges ...

Over the last decade, deep generative modelling has emerged as a powerful probabilistic tool in machine learning. The idea behind generative modelling is simple: transform noise to create new data that matches a given ...

Coding theory is concerned with the design and analysis of error-correcting codes, a method for protecting data from noise or corruption. In addition to their wide practical applicability, error-correcting codes are also ...

In machine learning, a field addressing the extraction of information and structure from finite data with the means of computer science and mathematics, maps from finite-dimensional spaces of data or computations into ...

This workshop in real and harmonic analysis surveyed recent investigations in areas including geometric measure theory and restriction theory, multiple ergodic averages, local smoothing estimates, Schrödinger and ...

Algebraic geometry has grown into a broad subject, with many different streams often advancing quite independently of each other. Nonetheless, important advances have often come from visionary applications of ideas in ...

Singularity theory concerns local and global structure of singularities of algebraic varieties and maps, often focusing on the interplay between algebraic geometry, symplectic topology, algebra, combinatorics, etc.

Over the last 30 years, there has been spectacular progress in deriving the well-known hydrodynamic limits from stochastic interacting particle systems, as well as characterizing the fluctuations of locally conserved quantities ...