Simon Fraser University

Functions appearing in many applications, for example as the solution of an integral or differential equation, are usually discretized and approximated in a basis. Each function in a certain space can be uniquely represented in that basis...

In this talk, we present a compressed sensing approach to sparse polynomial approximation via convex and non-convex optimization of functions in high dimensions. Of particular interest is the parameterized PDE setting, where the target function is...

Concentration waves of swimming bacteria Escherichia coli were described in his seminal paper by Adler (Science 1966). These experiments gave rise to intensive PDE modelling and analysis, after the original model by Keller and Segel (J. Theor. Biol...

We introduce an efficient algorithm, called partition of unity extension or PUX, to construct an extension of desired regularity of a function given on a complex multiply connected domain in $2D$.Function extension plays a fundamental role in...

Borcherds won the Fields medal in 1998 for his proof of the Monstrous Moonshine Conjecture. Loosely speaking, the conjecture asserts that the representation theory of the Monster, the largest sporadic finite simple group, is dictated by the Fourier...

The idea of this event is to offer graduate students in Statistics and Actuarial Science with an opportunity to attend a seminar with accessible talks providing them an introduction to active areas of research in the field. For three students from...

The approach of Nigel Gay for estimating the coverage of multivalent vaccine (MMR = measles, mumps, rubella) out antibody prevalence data leads to a polynomial system of equations of degree six describing a generically 2:1 covering of the 7...

An intriguing application of Deep Learning research is the use of Deep Convolutional Neural Networks (DCNNs) for image processing, as seen for example in the Prisma app and the Deep Dream algorithm. At SFU SIAT's iVizLab, we are using DCNNs within...

My talk will be on boundary integral methods, which is a class of powerful methods for solving certain elliptic PDEs, such as the Laplace, Helmholtz and Stokes equations. These methods require efficient and accurate evaluation of singular and nearly...

Talk details are available on the SFU DM site here