Seminario del 2025

Giugno
04
2025
Marcelo Pereyra
Bayesian imaging sciences: methods and algorithms
nel ciclo di seminari: BAYESIAN IMAGING SCIENCES: METHODS AND ALGORITHMS
analisi numerica
This teaching unit will introduce students to the Bayesian statistical framework for performing inference in high-dimensional inverse problems related to imaging sciences. We will start from basic concepts on probabilistic modelling, Bayesian decision theory, and Monte Carlo integration for Bayesian computation, and progress quickly to modern Bayesian imaging approaches. We will pay special attention to strategies based on stochastic diffusion processes and to Bayesian imaging models that combine elements derived from machine learning with elements derived from the physics of the considered imaging problem. The key ideas and techniques will be illustrated on imaging problems where we will conduct challenges inferences such as uncertainty quantification, hypothesis testing, model self-calibration, and model selection without ground truth.
organizzato da: International Ph.D. Summer School Mathematics and Machine Learning for Image Analysis
nell'ambito del Progetto Fondi U.E. BPIS_2024_MORIGI Mathematics and Machine Learning for image analysis (ERASMUS+) del prof. Serena Morigi

indietro