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  1. No Access

    Chapter and Conference Paper

    Splitting Structural and Semantic Knowledge in Graph Autoencoders for Graph Regression

    This paper introduces ReGenGraph, a new method for graph regression that combines two well-known modules: an autoencoder and a graph autoencoder. The main objective of our proposal is to split the knowledge in...

    Sarah Fadlallah, Natália Segura Alabart… in Graph-Based Representations in Pattern Rec… (2023)

  2. No Access

    Chapter and Conference Paper

    Graph Regression Based on Graph Autoencoders

    We offer in this paper a trial of encoding graph data as means of efficient prediction in a parallel setup. The first step converts graph data into feature vectors through a Graph Autoencoder (G-AE). Then, der...

    Sarah Fadlallah, Carme Julià… in Structural, Syntactic, and Statistical Pat… (2022)