This course provides doctoral students the foundations of applied probability and stochastic modeling. The first part of the course covers basic concepts in probability, such as the Borel Cantelli ...

Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...

The study of gradient flows and large deviations in stochastic processes forms a vital link between microscopic randomness and macroscopic determinism. By characterising how systems evolve in response ...

Students must have completed or currently enrolled in a course in the equivalency group containing MATH 310-2 or MATH 311-2. Prerequisite: Students must have completed or currently enrolled in a ...

Applications range from medical imaging to autonomous vehicle technology. Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic ...

Ivan Bajic (ibajic at ensc.sfu.ca) Office hours: Monday and Wednesday, 13:00-14:00 online (Zoom, see the link in course materials) Introduction to the theories of probability and random variables, and ...

This course is compulsory on the MSc in Quantitative Methods for Risk Management. This course is available on the MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in ...

A mathematician who developed formulas to make random processes more predictable and helped to solve an iconic model of complex phenomena has won the 2024 Abel Prize, one of the field’s most coveted ...

Ivan Bajic (ibajic at ensc.sfu.ca) Office hours: Monday and Wednesday, 13:00-14:00 online (Zoom, see the link in course materials) Introduction to the theories of probability and random variables, and ...