Bayesian methods are emerging as a powerful and flexible framework for many signal processing applications. The Bayesian framework provides principled ways to incorporate prior knowledge, perform inference and learning, and process uncertainties of any kind. Still, Bayesian methods have been challenging to scale up to high-dimensional data, making them computationally demanding for real-time applications.
This special session aims to bring together researchers and practitioners to present recent advances in efficient Bayesian methods for signal processing and their applications, including speech and audio processing, image processing, and biomedical image processing, among others. Moreover, the proposed special session will provide a platform for researchers and practitioners to foster collaborations on efficient Bayesian methods for signal processing.
Organizers: Bert de Vries (Eindhoven University of Technology, Netherlands), Francesco A.N. Palmieri, Giovanni Di Gennaro (Università degli Studi della Campania “Luigi Vanvitelli”, Aversa, Italy), Amedeo Buonanno (Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Portici, Italy)