Special Events and Conferences

Tutorials Lecturer: Malena Español

Tutorial Lecture: Intro to Inverse Problems: The Image Deblurring Problem

Description: Inverse problems are situations where hidden information is computed from external observations. For instance, in image deblurring, we aim to recover a clear image from one that is blurred and noisy. This first tutorial will explore how matrices and vectors naturally model discrete, ill-posed inverse problems, using linear algebra techniques to understand the inherent challenges. We will then introduce filtering and variational approaches to regularize these problems, effectively allowing us to recover useful information from seemingly distorted data.

Tutorials Lecturer: Ricardo Baptista

Tutorial Lecture: Data Assimilation Problems: Inverse Problems with time

Description: Data assimilation combines observations and model predictions to improve our understanding and forecasting of evolving systems, making it an essential tool in fields like meteorology, climate science, and engineering. This approach treats time as a key variable, continually integrating incoming data into a model to adjust predictions and correct for uncertainty. In this tutorial, we will explore data assimilation as a type of time-dependent inverse problem by using concepts from dynamical systems and probability to reconstruct the state of a system from predictive models and observational data.