All Events
Implicit-Explicit Time Integration for Multiscale Physics
Dr. Debojyoti Ghosh
Postdoctoral Research Staff Member
Abstract: Physical phenomena are often characterized by a large range of temporal scales. Unsteady simulations of these phenomena using explicit time integration may be inefficient if the fastest time scales in the model are not of practical interest. Implicit time integration can be... Read More
Model Based Clustering Using Multiple Scaled Distributions
Cristina Tortora
Abstract: Cluster analysis aims to identify homogeneous groups of units, called clusters, within data. Model-based clustering methods consider the overall population as a mixture of groups and each component of this mixture is modeled through its conditional probability distribution. ... Read More
Filtering as Gradient Descent
Abhishek Halder
Assistant Professor, Department of Applied Mathematics and Statistics
Abstract: Filtering, or dynamic state estimation, is a central problem in many areas of engineering including control, robotics, and signal processing. Historically, both the theory and algorithms for filtering have been developed from a transport or PDE viewpoint. While successful in many... Read More
