Davide Bacciu

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Alessio MicheliDepartment of Computer Science, University of PisaVerified email at di.unipi.it
Claudio GallicchioTenure Track Assistant Professor at the Department of Computer Science, University of PisaVerified email at di.unipi.it
Antonio CartaAssistant Professor @ Università di PisaVerified email at unipi.it
Vincenzo LomonacoAssistant Professor @ Unipi, Founding Board Member @ ContinualAI.org, Co-Founder @ ContinualIST.comVerified email at unipi.it
Federico ErricaSenior Research Scientist, NEC Laboratories EuropeVerified email at neclab.eu
Marco PoddaAssistant Professor, University of PisaVerified email at unipi.it
Stefano ChessaFull Professor, Department of Computer Science, University of PisaVerified email at di.unipi.it
Andrea CossuAssistant Professor, University of PisaVerified email at unipi.it
Alessandro SperdutiUniversity of PadovaVerified email at math.unipd.it
Alessandro SaffiottiProfessor of Computer Science, University or Örebro, SwedenVerified email at aass.oru.se
Mauro DragoneAssociate Professor, Heriot-Watt University, Edinburgh, Scotland, UKVerified email at hw.ac.uk
Paulo Lisboaliverpool john moores universityVerified email at ljmu.ac.uk
Andrea ValentiUniversità di PisaVerified email at phd.unipi.it
Danilo NumerosoAI Research Scientist, iGeniusVerified email at igenius.ai
Claudio VairoResearcher at ISTI-CNRVerified email at isti.cnr.it
Claudio GennaroISTI-CNR, PisaVerified email at isti.cnr.it
Alessio GravinaUniversity of PisaVerified email at phd.unipi.it
Maurizio Di RoccoPostdoc Örebro University, AASS centerVerified email at aass.oru.se
Daniele CastellanaResearch Fellow at University of FlorenceVerified email at unifi.it
Giuseppe AmatoDirector of Research - ISTI - Consiglio Nazionale delle RicercheVerified email at isti.cnr.it

Davide Bacciu

Dipartimento di Informatica, Università di Pisa

Verified email at di.unipi.it - Homepage

Deep Learning Generative Models Graph Representation Learning Continual Learning Pervasive AI


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A fair comparison of graph neural networks for graph classification F Errica, M Podda, D Bacciu, A Micheli Proceedings of the 8th International Conference on Learning Representations …, 2019	516	2019
A gentle introduction to deep learning for graphs D Bacciu, F Errica, A Micheli, M Podda Neural Networks 129, 203-221, 2020	321	2020
Avalanche: an end-to-end library for continual learning V Lomonaco, L Pellegrini, A Cossu, A Carta, G Graffieti, TL Hayes, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	198	2021
Internet of robotic things–converging sensing/actuating, hyperconnectivity, artificial intelligence and IoT platforms O Vermesan, A Bröring, E Tragos, M Serrano, D Bacciu, S Chessa, ... Cognitive hyperconnected digital transformation, 97-155, 2022	139	2022
An experimental characterization of reservoir computing in ambient assisted living applications D Bacciu, P Barsocchi, S Chessa, C Gallicchio, A Micheli Neural Computing and Applications 24, 1451-1464, 2014	139	2014
Continual Learning for Recurrent Neural Networks: an Empirical Evaluation A Cossu, A Carta, V Lomonaco, D Bacciu Neural Networks 143, 607-627, 2021	105	2021
Contextual graph markov model: A deep and generative approach to graph processing D Bacciu, F Errica, A Micheli International conference on machine learning, 294-303, 2018	98	2018
Learning from humans how to grasp: a data-driven architecture for autonomous grasping with anthropomorphic soft hands C Della Santina, V Arapi, G Averta, F Damiani, G Fiore, A Settimi, ... IEEE Robotics and Automation Letters 4 (2), 1533-1540, 2019	90	2019
A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor M Podda, D Bacciu, A Micheli, R Bellù, G Placidi, L Gagliardi Scientific reports 8 (1), 13743, 2018	86	2018
A deep generative model for fragment-based molecule generation M Podda, D Bacciu, A Micheli International conference on artificial intelligence and statistics, 2240-2250, 2020	70	2020
Robotic ubiquitous cognitive ecology for smart homes G Amato, D Bacciu, M Broxvall, S Chessa, S Coleman, M Di Rocco, ... Journal of Intelligent & Robotic Systems 80, 57-81, 2015	51	2015
Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees D Bacciu, A Micheli, A Sperduti IEEE Transactions on Neural Networks and Learning Systems 23 (12), 1987 - 2002, 2012	49	2012
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks A Gravina, D Bacciu, C Gallicchio Proceedings of the Eleventh International Conference on Learning …, 2023	47	2023
Continual pre-training mitigates forgetting in language and vision A Cossu, A Carta, L Passaro, V Lomonaco, T Tuytelaars, D Bacciu Neural Networks 179, 106492, 2024	46	2024
Edge-based sequential graph generation with recurrent neural networks D Bacciu, A Micheli, M Podda Neurocomputing 416, 177-189, 2020	41	2020
An experience in using machine learning for short-term predictions in smart transportation systems D Bacciu, A Carta, S Gnesi, L Semini Journal of Logical and Algebraic Methods in Programming 87, 52-66, 2017	41	2017
A learning system for automatic Berg Balance Scale score estimation D Bacciu, S Chessa, C Gallicchio, A Micheli, L Pedrelli, E Ferro, ... Engineering Applications of Artificial Intelligence 66, 60-74, 2017	40	2017
Distilled replay: Overcoming forgetting through synthetic samples A Rosasco, A Carta, A Cossu, V Lomonaco, D Bacciu International Workshop on Continual Semi-Supervised Learning, 104-117, 2021	39	2021
MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks D Numeroso, D Bacciu 2021 International Joint Conference on Neural Networks (IJCNN 2021), 1-8, 2021	39	2021
Detecting adversarial examples through nonlinear dimensionality reduction F Crecchi, D Bacciu, B Biggio In 27th European Symposium on Artificial Neural Networks, Computational …, 2019	37	2019

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