Activities
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Prof Anna-Karin Tornberg (KTH Stockholm)
Layer potentials – quadrature error estimates and approximation with error control When numerically solving PDEs reformulated as integral equations, so-called layer potentials must be evaluated. The quadrature error associated with a regular quadrature rule for evaluation of such integrals increases rapidly when the evaluation point approaches the surface and the integrand becomes sharply peaked. Error…
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Professor Yang-hui He (London Institute for Mathematical Sciences and University of Oxford)
The AI Mathematician We argue how AI can assist mathematics in three ways: theorem-proving,conjecture formulation, and language processing.Inspired by initial experiments in geometry and string theory in 2017, we summarize how thisemerging field has grown over the past years, and show how various machine-learningalgorithms can help with pattern detection across disciplines ranging from algebraicgeometry to…
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Prof. Sir David Spiegelhalter FRS OBE (University of Cambridge)
Chance, luck, and ignorance; how to put our uncertainty into numbers We all have to live with uncertainty about what is going to happen, what has happened, and why things turned out how they did. We attribute good and bad events as ‘due to chance’, label people as ‘lucky’, and (sometimes) admit our ignorance. I will…
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Prof. Mark Jerrum (Queen Mary University London)
Perfect sampling, old and new The possibility of obtaining perfect samples efficiently from a complex probability distribution entered the consciousness of the community in the mid-nineties with the invention of `coupling from the past’ by Propp and Wilson. The study of perfect samplers of course has considerable theoretical appeal. But, in addition, their ‘self clocking’…
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Prof. Benjamin Doyon (King’s College London)
The emergence of hydrodynamics in many-body systems One of the most important problems of modern science is that of emergence. How do laws of motion emerge at large scales of space and time, from much different laws at small scales? Hydrodynamics offers a basic but very relevant example. Molecules in air simply go along their…
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Prof. John Baez (University of California, Riverside)
Category Theory in Epidemiology “Stock and flow diagrams” are widely used for modeling in epidemiology. Modelers often regard these diagrams as an informal step toward a mathematically rigorous formulation of a model in terms of ordinary differential equations. However, these diagrams have a precise syntax, which can be explicated using category theory. Although commercial tools…
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Prof. Raúl Tempone (RWTH Aachen University and KAUST)
Navigating the Unknown: Harnessing Uncertainty in Renewable Energy and Heart Health Uncertainty Quantification (UQ) emerges as a guiding force in the turbulent sea of data-driven domains, from energy to health. This talk presents a methodology that harnesses UQ for robust renewable energy forecasting, employing a stochastic differential equation model that sails beyond the challenges of…
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Prof. Rachel Norman FRSE (University of Stirling)
Deconstructing beta: Using mathematical models to understand disease transmission and control – (Stirling) In this talk we will look at mathematical models of infectious diseases and how we model disease transmission and hence understand disease control for a series of case studies. Starting with the simple models that you will be familiar with since covid…
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Prof. Susanna Terracini (ICMS and Heriot-Watt University)
Pattern Formation Through Spatial Segregation
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Steven Tobias (University of Edinburgh)
From Order to Chaos and Chaos to Order in Fluid Flows The eleven year solar activity cycle is a remarkable example of regular behaviour emerging from an extremely turbulent system. The jets on Jupiter sit unmoving on a sea of turbulent eddies. Astrophysical phenomena often display organisation on spatial and temporal scales much larger than…