Davide Bacciu

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Coauteurs

Alessio MicheliDepartment of Computer Science, University of PisaAdresse e-mail validée de di.unipi.it
Claudio GallicchioAssociate Professor at the Department of Computer Science, University of PisaAdresse e-mail validée de unipi.it
Antonio CartaAssistant Professor @ Università di PisaAdresse e-mail validée de unipi.it
Vincenzo LomonacoTenure-Track Researcher @ Unipi, Founder @ ContinualAI.org, Founder & CEO @ ContinualIST.comAdresse e-mail validée de unipi.it
Federico ErricaSenior Research Scientist, NECAdresse e-mail validée de neclab.eu
Andrea CossuAssistant Professor, University of PisaAdresse e-mail validée de unipi.it
Marco PoddaAssistant Professor, University of PisaAdresse e-mail validée de unipi.it
Stefano ChessaFull Professor, Department of Computer Science, University of PisaAdresse e-mail validée de di.unipi.it
Alessandro SperdutiUniversity of PadovaAdresse e-mail validée de math.unipd.it
Alessandro SaffiottiProfessor of Computer Science, University or Örebro, SwedenAdresse e-mail validée de aass.oru.se
Mauro DragoneAssociate Professor, Heriot-Watt University, Edinburgh, Scotland, UKAdresse e-mail validée de hw.ac.uk
Paulo Lisboaliverpool john moores universityAdresse e-mail validée de ljmu.ac.uk
Alessio GravinaUniversity of PisaAdresse e-mail validée de di.unipi.it
Andrea ValentiUniversità di PisaAdresse e-mail validée de phd.unipi.it
Danilo NumerosoAI Research Scientist, iGeniusAdresse e-mail validée de igenius.ai
Claudio VairoResearcher at ISTI-CNRAdresse e-mail validée de isti.cnr.it
Claudio GennaroISTI-CNR, PisaAdresse e-mail validée de isti.cnr.it
Cosimo Della SantinaDelft University of Technology (TU Delft), German Aerospace Center (DLR)Adresse e-mail validée de dlr.de
Maurizio Di RoccoPostdoc Örebro University, AASS centerAdresse e-mail validée de aass.oru.se
Daniele CastellanaResearch Fellow at University of FlorenceAdresse e-mail validée de unifi.it

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Davide Bacciu

Professor @ Università di Pisa - Founder & Chief Scientist @ ContinualIST.com

Adresse e-mail validée de di.unipi.it - Page d'accueil

Deep Learning Generative Models Graph Representation Learning Continual Learning Pervasive AI


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	558	2019
A gentle introduction to deep learning for graphs D Bacciu, F Errica, A Micheli, M Podda Neural Networks 129, 203-221, 2020	353	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	214	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	152	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	140	2014
Continual Learning for Recurrent Neural Networks: an Empirical Evaluation A Cossu, A Carta, V Lomonaco, D Bacciu Neural Networks 143, 607-627, 2021	123	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	100	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	96	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	89	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	78	2020
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	63	2024
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	62	2023
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	52	2012
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
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	47	2021
Sample condensation in online continual learning M Sangermano, A Carta, A Cossu, D Bacciu 2022 International Joint Conference on Neural Networks (IJCNN), 01-08, 2022	45	2022
Edge-based sequential graph generation with recurrent neural networks D Bacciu, A Micheli, M Podda Neurocomputing 416, 177-189, 2020	45	2020
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	43	2017
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	43	2017
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	42	2021

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