Graph Signal Processing and Graph Neural Networks

Graph signal processing aims to develop tools for processing data defined in irregular graphic domains. Graphs offer the ability to model this information and create complex interactions between. Graph Neural Networks (GNN) are a type of deep learning method designed to make inference from the information described by graphs.

These are the services that our research groups can develop. For customized information on the services, please contact us.

Areas of service	Applications of the service	Scientific infrastructure
Learning over networks, graph topology inference, source identification, graph sampling and reconstruction	Social media, sensor networks, brain network analysis, smart grid

system optimisation, privacy, sensors, brain network analysis, smart grids, graph sampling, graph topology, learning networks

Artificial Inteligence - AI

Keywords Graph signal processing and graph neural networks