Graph Geometric Algebra networks for graph representation learning
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-024-84483-0
Abstract: Graph neural networks (GNNs) have emerged as a prominent approach for capturing graph topology and modeling vertex-to-vertex relationships. They have been widely used in pattern recognition tasks including node and graph label prediction. However, when… read more here.
Keywords: graph geometric; networks graph; algebra; learning graph ... See more keywords
Morpho-statistical description of networks through graph modelling and Bayesian inference
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3155359
Abstract: Collaboration graphs are relevant sources of information to understand behavioural tendencies of groups of individuals. The study of these collaboration graphs enables figuring out factors that may affect the efficiency and the sustainability of cooperative… read more here.
Keywords: description networks; networks graph; statistical description; inference ... See more keywords
Graph Distributional Signals for Regularization in Graph Neural Networks
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DOI: 10.1109/tsipn.2025.3587400
Abstract: In graph neural networks (GNNs), both node features and labels are examples of graph signals. While it is common in graph signal processing to impose signal smoothness constraints in learning and estimation tasks, it is… read more here.
Keywords: graph distributional; distributional signals; networks graph; graph neural ... See more keywords