Search Results for author: Miquel Ferriol-Galmés

Found 4 papers, 1 papers with code

Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities

no code implementations29 Dec 2021 José Suárez-Varela, Paul Almasan, Miquel Ferriol-Galmés, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, Pere Barlet-Ros

Graph neural networks (GNN) have shown outstanding applications in many fields where data is fundamentally represented as graphs (e. g., chemistry, biology, recommendation systems).

Recommendation Systems

Scaling Graph-based Deep Learning models to larger networks

no code implementations4 Oct 2021 Miquel Ferriol-Galmés, José Suárez-Varela, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio

Graph Neural Networks (GNN) have shown a strong potential to be integrated into commercial products for network control and management.

Applying Graph-based Deep Learning To Realistic Network Scenarios

no code implementations13 Oct 2020 Miquel Ferriol-Galmés, José Suárez-Varela, Pere Barlet-Ros, Albert Cabellos-Aparicio

Recent advances in Machine Learning (ML) have shown a great potential to build data-driven solutions for a plethora of network-related problems.

Cannot find the paper you are looking for? You can Submit a new open access paper.