What is Pattern?
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Pattern is ubiquitous and seems totally familiar. Yet if we ask what it is, we find a bewildering collection of answers. Here we suggest that there is a common thread, and it revolves around dynamics.
Computer Science
Connection to other fields Image:
Biological Shape Analysis with Geometric Statistics and Learning
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The advances in biomedical imaging techniques have enabled us to access the 3D shapes of a variety of structures: organs, cells, proteins. Since biological shapes are related to physiological functions, shape data may hold the key to unlocking outstanding mysteries in biomedicine. This snapshot introduces the mathematical framework of geometric statistics and learning and its applications to biomedicine.
Solving inverse problems with Bayes’ theorem
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The goal of inverse problems is to find an unknown parameter based on noisy data. Such problems appear in a wide range of applications including geophysics, medicine, and chemistry. One method of solving them is known as the Bayesian approach. In this approach, the unknown parameter is modelled as a random variable to reflect its uncertain value. Bayes’ theorem is applied to update our knowledge given new information from noisy data.
Invitation to quiver representation and Catalan combinatorics
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Representation theory is an area of mathematics that deals with abstract algebraic structures and has nu- merous applications across disciplines. In this snap- shot, we will talk about the representation theory of a class of objects called quivers and relate them to the fantastic combinatorics of the Catalan numbers.
Searching for structure in complex data: A modern statistical quest
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Shape space - a paradigm for character animation in computer graphics
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Nowadays 3D computer animation is increasingly realistic as the models used for the characters become more and more complex. These models are typically represented by meshes of hundreds of thousands or even millions of triangles. The mathematical notion of a shape space allows us to effectively model, manipulate, and animate such meshes. Once an appropriate notion of dissimilarity measure between different triangular meshes is defined, various useful tools in character modeling and animation turn out to co- incide with basic geometric operations derived from this definition
La La Lab - The Mathematics of Music
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We describe a journey through our exhibition La La Lab - the Mathematics of Music, which mixes a laboratory format with interactive exhibits to present visitors with the historical, conceptual, and artistic connections between mathematics and music, pushing forward musical creativity, mathematical knowledge and any blending of the two.
Is it possible to predict the far future before the near future is known accurately?
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It has always been the dream of mankind to predict the future. If the future is governed by laws of physics, like in the case of the weather, one can try to make a model, solve the associated equations, and thus predict the future. However, to make accurate predictions can require extremely large amounts of computation. If we need seven days to compute a prediction for the weather tomorrow and the day after tomorrow, the prediction arrives too late and is thus not a prediction any more.
Analogue mathematical instruments: Examples from the “theoretical dynamics” group (France, 1948–1964)
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Throughout the history of dynamical systems, instruments have been used to calculate and visualize (approximate) solutions of differential equations. Here we describe the approach of a group of physicists and engineers in the period 1948–1964, and we give ex- amples of the specific (analogue) mathematical in- struments they conceived and used. These examples also illustrate how their analogue culture and practices faced the advent of the digital computer, which appeared at that time as a new instrument, full of promises.
Deep Learning and Inverse Problems
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Big data and deep learning are modern buzz words which presently infiltrate all fields of science and technology. These new concepts are impressive in terms of the stunning results they achieve for a large variety of applications. However, the theoretical justification for their success is still very limited. In this snapshot, we highlight some of the very recent mathematical results that are the beginnings of a solid theoretical foundation for the subject.