15 - 07/2021 10 09/2021

PDE and Randomness

Organisers: Professor Hendrik Weber
Dr Andris Gerasimovics

PDE and Randomness symposium, 1st - 10th of September 2021, University of Bath, UK

14 - 30 07/2021

Analytic and Geometric Approaches to Machine Learning

Organisers: Dr Matthew Thorpe (The University of Manchester)
Dr Patricia Vitoria Carrera (Universitat Pompeu Fabra, Barcelona)
Dr Bamdad Hosseini (California Institute of Technology)

The aim of the workshop is to bring together researchers that apply mathematical methodology to machine learning. We particularly want to emphasise how mathematical theory can inform applications and vice versa.
This workshop is the first of two workshops on this topic. The second will be an in-person workshop to be held at ...

14 - 23 07/2021

LMS-INI- Bath Summer School on K-Theory & Representation Theory

Organisers: Dr. Haluk Şengün, University of Sheffield
Prof. Roger Plymen, University of Manchester
Prof. Nigel Higson, PennState University

This is the summer school part of the LMS-INI-Bath Symposium on K-theory and Representation Theory (which will take place in July 2022). In this summer school, we will cover material that is foundational to the upcoming symposium, namely, representation theory of real and p-adic Lie groups, the theory of C*-algebras and operator K-theory, and fi...

12 - 07 07/2021

Mathematics of Machine Learning

Organisers: Philip Aston, University of Surrey, UK
Matthias J. Ehrhardt, University of Bath, UK
Catherine Higham, University of Glasgow, UK
Clarice Poon, University of Bath, UK

Machine Learning (ML) can described as statistical and numerical methods which underpin modern algorithms for detecting patterns and inference. A common theme to many activities in ML today is that mathematical models based on sample data are used to train algorithms to work on real data. Applications include self-driven cars, fraud detection, a...

Load More