Mon, 09 Mar 2020
12:45
L3

Bottom-up construction of 4d N=2 SCFTs

Carlo Meneghelli
(Oxford)
Abstract

In this talk, I will argue how the observation that four-dimensional N=2 superconformal field theories are interconnected via the operation of Higgsing can be turned into an effective method to construct such SCFTs. A fundamental role is played by the (generalized) free field realization of the associated VOAs.

Towards verifiable and safe model-free reinforcement learning
Hasanbeig, M Kroening, D Abate, A Proceedings of the 1st Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis (OVERLAY 2019) volume 2509 (03 Mar 2020)
Thu, 05 Mar 2020

15:00 - 16:00
C4

Connections in symplectic topology

Todd Liebenschutz-Jones
Abstract

Here, a connection is a algebraic structure that is weaker than an algebra and stronger than a module. I will define this structure and give examples. I will then define the quantum product and explain how connections capture important properties of this product. I will finish by stating a new result which describes how this extends to equivariant Floer cohomology. No knowledge of symplectic topology will be assumed in this talk.
 

Wed, 27 May 2020

17:00 - 18:00
L1

Philip Maini: Squirrels, Turing and Excitability - Mathematical Modelling in Biology, Ecology and Medicine

Philip Maini
(University of Oxford)
Further Information

Mathematical modelling lives a varied life. It links the grey squirrel invasion in the UK to the analysis of how tumour cells invade the body; Alan Turing's model for pattern formation gives insight into animal coat markings and Premier League Football Shirts; and models for Excitability have been used to model the life cycle of the cellular slime mold and heart attacks.

Philip Maini will reveal all in our latest Oxford Mathematics Public Lecture.

Philip Maini is Professor of Mathematical Biology in the University of Oxford.

Watch live:
https://twitter.com/OxUniMaths
https://www.facebook.com/OxfordMathematics/
https://livestream.com/oxuni/Maini

The Oxford Mathematics Public Lectures are generously supported by XTX Markets.

Wed, 04 Mar 2020
14:00
N3.12

Machine Learning with Hawkes Processes

Saad Labyad
(Oxford University)
Abstract

Hawkes processes are a class of point processes used to model self-excitation and cross-excitation between different types of events. They are characterized by the auto-regressive structure of their conditional intensity, and there exists several extensions to the original linear Hawkes model. In this talk, we start by defining Hawkes processes and give a brief overview of some of their basic properties. We then review some approaches to parametric and non-parametric estimation of Hawkes processes and discuss some applications to problems with large data sets in high frequency finance and social networks.

Analytic results for deep-inelastic scattering at NNLO QCD with the nested soft-collinear subtraction scheme
Asteriadis, K Caola, F Melnikov, K Röntsch, R European Physical Journal C volume 80 issue 1 8 (03 Jan 2020)
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