## Search

## QM^{3} Quantum Matter meets Maths

Anderson localization and local eigenvalue statistics.

*Svetlana Jitomirskaya*, University of California, Irvine.

## Geometria em Lisboa

Lagrangian cobordism and Chow groups.

*Nick Sheridan*, University of Edinburgh.

## Abstract

Homological mirror symmetry predicts an equivalence of categories, between the Fukaya category of one space and the derived category of another. We can "decategorify" by taking the Grothendieck group of these categories, to get an isomorphism of abelian groups. The first of these abelian groups is related, by work of Biran-Cornea, to the Lagrangian cobordism group; the second is related, via the Chern character, to the Chow group. I will define the Lagrangian cobordism and Chow groups (which is much easier than defining the categories). Then I will describe joint work with Ivan Smith in which we try to compare them directly, and find some interesting analogies.

## Topological Quantum Field Theory

Homotopy Quantum Field Theories.

*Alexis Virelizier*, Université de Lille.

## QM^{3} Quantum Matter meets Maths

To be announced.

*Vincenzo Alba*, University of Amsterdam.

## Geometria em Lisboa

An invitation to Kähler-Einstein metrics and random point processes.

*Robert Berman*, Chalmers University of Technology.

## Topological Quantum Field Theory

Poisson sigma model and integrable systems.

*Nicolai Reshetikhin*, University of California, Berkeley.

## QM^{3} Quantum Matter meets Maths

To be announced.

*Gil Refael*, Institute for Quantum Information and Matter.

## Geometria em Lisboa

To be announced.

*Yang Li*, Institute for Advanced Study.

## Mathematics, Physics & Machine Learning

To be announced.

*Gitta Kutyniok*, Institut für Mathematik - TU Berlin.

## Topological Quantum Field Theory

Relative mapping class group representations via conformal nets.

*André Henriques*, University of Oxford.

## QM^{3} Quantum Matter meets Maths

Deformed Airy kernel determinants: from KPZ tails to initial data for KdV.

*Tom Claeys*, Université Catholique de Louvain.

## Abstract

Fredholm determinants associated to deformations of the Airy kernel are closely connected to the solution to the Kardar-Parisi-Zhang (KPZ) equation with narrow wedge initial data, and they also appear as largest particle distribution in models of positive-temperature free fermions. I will explain how logarithmic derivatives of the Fredholm determinants can be expressed in terms of a $2\times 2$ Riemann-Hilbert problem.

This Riemann-Hilbert representation can be used to derive precise lower tail asymptotics for the solution of the KPZ equation with narrow wedge initial data, refining recent results by Corwin and Ghosal, and it reveals a remarkable connection with a family of unbounded solutions to the Korteweg-de Vries (KdV) equation and with an integro-differential version of the Painlevé II equation.

## Geometria em Lisboa

Topology and the Yang Mills functional.

*Gonçalo Oliveira*, Universidade Federal Fluminense, Brasil.

## Probability and Statistics

From high dimensional space to a random low dimensional space.

*Conceição Amado*, Instituto Superior Técnico and CEMAT.

## Mathematics, Physics & Machine Learning

To be announced.

*Gunnar Carlsson*, Stanford University.

## Topological Quantum Field Theory

A solution of the Riemann-Hilbert problem on the $A_2$ quiver.

*Davide Masoero*, Group of Mathematical Physics, University of Lisbon.

## Geometria em Lisboa

To be announced.

*Éveline Legendre*, Université Paul Sabatier.

## Probability and Statistics

To be announced.

*Manuel Scotto*, Instituto Superior Técnico and CEMAT.

## Mathematics, Physics & Machine Learning

Machine Learning and Scientific Computing.

*Weinan E*, Princeton University.

## Topological Quantum Field Theory

Cluster realization of quantum groups and higher Teichmüller theory.

*Alexander Shapiro*, UC Berkeley.

## QM^{3} Quantum Matter meets Maths

To be announced.

*Masud Haque*, Maynooth University.

## Geometria em Lisboa

To be announced.

*Xiuxiong Chen*, ShanghaiTech University and Stony Brook University.

## Mathematics, Physics & Machine Learning

To be announced.

*Lindsey Gray*, Fermi National Accelerator Laboratory.

## Mathematics, Physics & Machine Learning

Combining knowledge and data driven methods for solving inverse imaging problems - getting the best from both worlds.

*Carola-Bibiane Schönlieb*, DAMTP, University of Cambridge.

## Abstract

Inverse problems in imaging range from tomographic reconstruction (CT, MRI, etc) to image deconvolution, segmentation, and classification, just to name a few. In this talk I will discuss

approaches to inverse imaging problems which have both a mathematical modelling (knowledge driven) and a machine learning (data-driven) component. Mathematical modelling is crucial in the presence of ill-posedness, making use of information about the imaging data, for narrowing down the search space. Such an approach results in highly generalizable reconstruction and analysis methods which come with desirable solutions guarantees. Machine learning on the other hand is a powerful tool for customising methods to individual data sets. Highly parametrised models such as deep neural networks in particular, are powerful tools for accurately modelling prior information about solutions. The combination of these two paradigms, getting the best from both of these worlds, is the topic of this talk, furnished with examples for image classification under minimal supervision and for

tomographic image reconstruction.

## Geometria em Lisboa

To be announced.

*Ana Rita Pires*, University of Edinburgh.

## Geometria em Lisboa

Stability of the symplectomorphism group of rational surfaces.

*Silvia Anjos*, Instituto Superior Técnico and CAMGSD.

## Mathematics, Physics & Machine Learning

Dealing with Systematic Uncertainties in HEP Analysis with Machine Learning Methods.

*Tommaso Dorigo*, Italian Institute for Nuclear Physics.