University of Calgary

One of the most important techniques provided by modern logic is the use of models to show the consistency of theories. The technique burst onto the scene in the late 19th century, and had its most important early instance in demonstrating the...

Any tangent category has a notion of connection for its differential bundles (the analog of vector bundles). In this talk, we’ll explore what this definition gives us in the tangent category of affine schemes. The talk will be roughly divided into...

Principal bundles arise in different areas of matematics with different definitions. However, they all have in common some kind of local triviality. Here I will present some work in progress on generalizing these in terms of join restriction...

In this project, we discuss some fine properties and the existence of variational solutions to the Total Variation Flow. Instead of the classical Euclidean setting, we intend to work mostly in the general setting of metric measure spaces. During the...

In the preface of its Lectures on Noncommutative Geometry [Gin05], Ginzburg writes: “Each of the mathematical worlds that we study is governed by an appropriate operad. Commutative geometry is governed by the operad of commutative (associative)...

Vertex operator algebras (VOAs) are a mathematical approach to quantum field theories which won their creator a Fields medal. But they are highly complicated structures -- if you haven't already learned what they are, it is surely best if you never...

Mathematics has developed an increasingly “higher dimensional” point of view of when different things deserve the same name, categorifying the traditional logical notion of equality to isomorphism (from Greek isos “equal” and morphe “form” or “shape”...

In this talk, I discuss a pure-exchange economy with no aggregate uncertainty, and I characterize in closed-form and in full generality Pareto-optimal risk-sharing allocations between two agents who maximize rank-dependent utilities (RDU). I then...

Machine Learning including deep learning techniques have been successfully used in many big-data fields. However, a limitation of many machine learning tools is that one needs to have a very large sample size to train a model with many parameters...

Foundational Methods in Computer Science is an annual workshop that brings together researchers in theoretical computer science and mathematics. Past workshops have been held at BIRS, Colgate University, Dalhousie University, Mount Allison University...