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Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification


Mar 22, 2021
Antonio Carta, Andrea Cossu, Federico Errica, Davide Bacciu

* Accepted at the 2021 Web Conference Workshop on Graph Learning Benchmarks (GLB 2021). Code available at https://github.com/diningphil/continual_learning_for_graphs 

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Graph Mixture Density Networks


Dec 05, 2020
Federico Errica, Davide Bacciu, Alessio Micheli


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Accelerating the identification of informative reduced representations of proteins with deep learning for graphs


Jul 14, 2020
Federico Errica, Marco Giulini, Davide Bacciu, Roberto Menichetti, Alessio Micheli, Raffaello Potestio


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Concept Matching for Low-Resource Classification


Jun 01, 2020
Federico Errica, Ludovic Denoyer, Bora Edizel, Fabio Petroni, Vassilis Plachouras, Fabrizio Silvestri, Sebastian Riedel


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Theoretically Expressive and Edge-aware Graph Learning


Jan 24, 2020
Federico Errica, Davide Bacciu, Alessio Micheli


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A Fair Comparison of Graph Neural Networks for Graph Classification


Jan 07, 2020
Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli

* Proceedings of the International Conference on Learning Representations (ICLR), 2020 

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A Gentle Introduction to Deep Learning for Graphs


Dec 29, 2019
Davide Bacciu, Federico Errica, Alessio Micheli, Marco Podda


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Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing


May 27, 2018
Davide Bacciu, Federico Errica, Alessio Micheli


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