Simon Fraser University

Uncertainty Quantification (UQ) is an increasingly popular subject in computational science and engineering, that deals with assessing the impact on the PDE solution of the uncertainty on the coefficients of the same PDE. Coefficients here is a term...

BC UMSC will take place during the last week of April 2019 at Simon Fraser University (Burnaby Campus). This inaugural event will provide Mathematics and Statistics Undergraduates with an opportunity to showcase their research, expand their learning...

This talk will focus on two topics in the foundations of neural networks: computability and false structures. In the first part I will recall briefly the concept of recursive functions and then discuss the gap between existence results, the...

What is a game? Mathematically speaking, a game has players, strategies and scores to explain why the players win or lose. Games which are modelled with differential equations are called differential games. Common examples are pursuit-evasion games...

Computational modelling can be used to reveal insights into the mechanisms of new drugs and to develop new diagnostic tools. Here I will discuss three major diseases: diabetes, hypertension, and autism. I will talk about how we construct models to...

This is the second of a two-part talk. In talk one, I will review various well-known algorithms for integer multiplication, such as schoolbook multiplication, Karatsuba multiplication, FFT multiplication, and the Schoenhage-Strassen algorithm. The...

In this first talk out of two, I will review various well-known algorithms for integer multiplication, such as schoolbook multiplication, Karatsuba multiplication, FFT multiplication, and the Schoenhage-Strassen algorithm. The talk will also be an...

We consider the problem of answering queries about formulas of first-order logic based on background knowledge partially represented explicitly as other formulas, and partially represented as examples independently drawn from a fixed probability...

The aim of structured optimization is to assemble a solution, using a given set of atoms, to fit a model to data. Polarity, which generalizes the notion of orthogonality from linear sets to general convex sets, plays a special role in a simple and...