Past SCAIM Seminars

Tue, 2017-11-21 12:30 - 13:30
Mike Irvine, Mathematics UBC
Complex individual-based models abound in epidemiology and ecology. Fitting these models to data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, and the complex models may take a long time to run, requiring parameter selection procedures. Approximate Bayesian Computation has been proposed as a likelihood-free method in resolving these issues, however requires careful selection of summary statistics and annealing scheme.
Tue, 2017-11-14 12:30 - 13:30
Tony Wong, Mathematics UBC
The eikonal equation is a fundamental nonlinear PDE that find vast applications. One particular example is to compute geodesic distance on a curved surface through solving an eikonal equation defined on the surface (surface eikonal equations). However, there are only very few literatures on solving surface eikonal equations numerically, due to the complication from the surface geometry. In this talk, we present a simple and efficient numerical algorithm to solve surface eikonal equations on general implicit surfaces.
Tue, 2017-10-31 12:30 - 13:30
Tom Eaves, Mathematics UBC
Transitional phenomena are ubiquitous in fluid dynamics and other nonlinear systems; they occur whenever there are multiple states in which a system can reside. Frequently, we are able to investigate when and how a system transitions from one state to another by performing a linear stability analysis and obtaining critical thresholds for various parameters beyond which our original state becomes "unstable". However, there are numerous examples for which such an approach does not work.
Tue, 2017-10-17 13:30 - 14:30
Bamdad Hosseini, Department of Mathematics, Simon Fraser University
Statistical and probabilistic methods are promising approaches to solving inverse problems – the process of recovering unknown parameters from indirect measurements. Of these, the Bayesian methods provide a principled approach to incorporating our existing beliefs about the parameters (the prior model) and randomness in the data. These approaches are at the forefront of extensive current investigation. Overwhelmingly, Gaussian prior models are used in Bayesian inverse problems since they provide mathematically simple and computationally efficient formulations of important inverse problems.
Tue, 2017-10-03 12:30 - 13:30
Eldad Haber, Department of Mathematics and Earth and Ocean Science, UBC
In this talk we will explore deep neural networks from a dynamical systems point of view. We will show that the learning problem can be cast as a path planning problem with PDE constraint. This opens the door to conventional Computational techniques that can speed up the learning process and avoid some of the local minima.
Tue, 2017-09-19 12:30 - 13:30
Uri Ascher, Department of Computer Science, The University of British Columbia
Visual computing is a wide area that includes computer graphics and image processing, where the ``eyeball-norm'' rules. I will briefly discuss two case studies involving numerical methods and analysis applied to this area. The first involves motion simulation and calibration of soft objects such as cloth, plants and skin. The governing elastodynamics PDE system, discretized in space already at the variational level using co-rotated FEM, leads to a large, expensive to assemble, dynamical system in time, where the damped motion may mask highly oscillatory stiffness.
Tue, 2017-08-29 12:30 - 13:30
Michael Overton, Courant Institute of Mathematical Sciences, New York University
In many applications one wishes to minimize an objective function that is not convex and is not differentiable at its minimizers. We discuss two algorithms for minimization of nonsmooth, nonconvex functions. Gradient Sampling is a simple method that, although computationally intensive, has a nice convergence theory. The method is robust and the convergence theory has recently been extended to constrained problems. BFGS is a well known method, developed for smooth problems, but which is remarkably effective for nonsmooth problems too.
Tue, 2017-06-13 12:30 - 14:00
Joshua Scurll, Department of Mathematics, The University of British Columbia
With super-resolution microscopy techniques such as Direct Stochastic Optical Reconstruction Microscopy (dSTORM), it is possible to image fluorescently labeled proteins on a cell membrane with high precision. Often, the extent to which such proteins cluster is biologically meaningful; for example, in B-cells, clustering of the B-cell receptor (BCR) is associated with increased intracellular signaling and B-cell activation, and spontaneous BCR clustering can cause chronic active BCR signaling that results in an aggressive B-cell malignancy.
Tue, 2017-05-30 12:30 - 14:00
Ailyn Stötzner, Faculty of Mathematics, TU Chemnitz
Elastoplastic deformations play a tremendous role in industrial forming. Many of these processes happen at non-isothermal conditions.Therefore, the optimization of such problems is of interest not only mathematically but also for applications. In this talk we will present the analysis of the existence of a global solution of an optimal control problem governed by a thermovisco(elasto)plastic model. We will point out the difficulties arising from the nonlinear coupling of the heat equation with the mechanical part of the model.
Tue, 2017-04-25 12:30 - 14:00
Paul Tupper, Mathematics, SFU
One important construction in the theory of metric spaces is the tight span. The tight span of a metric space can be thought of as a generalization of the idea of a convex hull in linear spaces and is the basis for much work in the study and visualization of finite metric spaces. Motivated by problems in phylogenetics, we have developed a generalization of the concept of metric spaces, which we call diversities. In a diversity, every subset of points in the space corresponds to a number, not just pairs, and there is a more general version of the triangle inequality.
Templates provided by UBC Department of Physics & Astronomy

a place of mind, The University of British Columbia

Faculty of Science
Institute of Applied Mathematics
311-6356 Agricultural Road
Vancouver, BC V6T 1Z2
Tel 604.822.8571
Fax 604.822.0957

Emergency Procedures | Accessibility | Contact UBC | © Copyright The University of British Columbia