Submitted by S.E. Morgan on Tue, 07/12/2021 - 13:42
This DEGAS Webinar Series is an event initiated by the IEEE SPS Data Science Initiative. The goal is to provide the SP community with updates and advances in learning and inference on graphs. Signal processing and machine learning often deal with data living in regular domains such as space and time. This webinar series will cover the extension of these methods to network data, including topics such as graph filtering, graph sampling, spectral analysis of network data, graph topology identification, geometric deep learning, and so on. Applications can for instance be found in image processing, social networks, epidemics, wireless communications, brain science, recommender systems, and sensor networks.
For more information and a list of upcoming talks, please see: https://dsiseminar.github.io/