Publications

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2021

Bacciu, Davide; Bianchi, Filippo Maria; Paassen, Benjamin; Alippi, Cesare

Deep learning for graphs Conference Forthcoming

Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021), Forthcoming.

BibTeX | Tags: deep learning, deep learning for graphs, graph data, structured data processing

Valenti, Andrea; Berti, Stefano; Bacciu, Davide

Calliope - A Polyphonic Music Transformer Conference Forthcoming

Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021), Forthcoming.

BibTeX | Tags: artificial creativity, autoencoder, deep learning, generative model, music generation, transformer

Bacciu, Davide; Conte, Alessio; Grossi, Roberto; Landolfi, Francesco; Marino, Andrea

K-Plex Cover Pooling for Graph Neural Networks Journal Article

Data Mining and Knowledge Discovery, 2021, (Accepted also as paper to the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2021)).

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, graph pooling, structured data processing

Cossu, Andrea; Carta, Antonio; Lomonaco, Vincenzo; Bacciu, Davide

Continual Learning for Recurrent Neural Networks: an Empirical Evaluation Journal Article Forthcoming

Neural Networks, Forthcoming.

Abstract | Links | BibTeX | Tags: Continual learning, deep learning, recurrent neural network, Sequential data

Andrea Rosasco Antonio Carta, Andrea Cossu Vincenzo Lomonaco Davide Bacciu

Distilled Replay: Overcoming Forgetting through Synthetic Samples Workshop Forthcoming

IJCAI 2021 workshop on continual semi-supervised learning (CSSL 2021) , Forthcoming.

Links | BibTeX | Tags: Continual learning, dataset distillation, deep learning

Bacciu, Davide; Podda, Marco

GraphGen-Redux: a Fast and Lightweight Recurrent Model for Labeled Graph Generation Conference Forthcoming

Proceedings of the International Joint Conference on Neural Networks (IJCNN 2021), IEEE Forthcoming.

BibTeX | Tags: deep learning, deep learning for graphs, generative model, graph data

Lomonaco, Vincenzo; Pellegrini, Lorenzo; Cossu, Andrea; Carta, Antonio; Graffieti, Gabriele; Hayes, Tyler L; Lange, Matthias De; Masana, Marc; Pomponi, Jary; van de Ven, Gido; Mundt, Martin; She, Qi; Cooper, Keiland; Forest, Jeremy; Belouadah, Eden; Calderara, Simone; Parisi, German I; Cuzzolin, Fabio; Tolias, Andreas; Scardapane, Simone; Antiga, Luca; Amhad, Subutai; Popescu, Adrian; Kanan, Christopher; van de Weijer, Joost; Tuytelaars, Tinne; Bacciu, Davide; Maltoni, Davide

Avalanche: an End-to-End Library for Continual Learning Workshop Forthcoming

Proceedings of the CVPR 2021 Workshop on Continual Learning , Forthcoming.

Links | BibTeX | Tags: Continual learning, deep learning, software

Castellana, Daniele; Bacciu, Davide

A Tensor Framework for Learning in Structured Domains Journal Article Forthcoming

Neurocomputing, Forthcoming.

BibTeX | Tags: deep learning, structured data processing, tensor factorization, tensor neural networks, tree structured data

Carta, Antonio; Sperduti, Alessandro; Bacciu, Davide

Encoding-based Memory for Recurrent Neural Networks Journal Article

Neurocomputing, 2021.

Abstract | Links | BibTeX | Tags: autoencoder, deep learning, memory networks, recurrent neural network, Sequential data

Errica, Federico; Giulini, Marco; Bacciu, Davide; Menichetti, Roberto; Micheli, Alessio; Potestio, Raffaello

A deep graph network-enhanced sampling approach to efficiently explore the space of reduced representations of proteins Journal Article

Frontiers in Molecular Biosciences, 8 , pp. 136, 2021.

Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, structured data processing

Andrea Valenti Michele Barsotti, Davide Bacciu ; Ascari, Luca

A Deep Classifier for Upper-Limbs Motor Anticipation Tasks in an Online BCI Setting Journal Article

Bioengineering , 2021.

Links | BibTeX | Tags: autoencoder, biomedical data, deep learning, Sequential data

2020

Ronchetti, Matteo; Bacciu, Davide

Generative Tomography Reconstruction Workshop

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Workshop on Deep Learning and Inverse Problems, 2020.

Abstract | Links | BibTeX | Tags: adversarial learning, biomedical data, deep learning, generative model, inverse problems, machine vision

Bacciu, Davide; Conte, Alessio; Grossi, Roberto; Landolfi, Francesco; Marino, Andrea

K-plex Cover Pooling for Graph Neural Networks Workshop

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Workshop on Learning Meets Combinatorial Algorithms, 2020.

Abstract | BibTeX | Tags: deep learning, deep learning for graphs, graph data, graph pooling, structured data processing

Carta, Antonio; Sperduti, Alessandro; Bacciu, Davide

Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization Workshop

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Workshop on Beyond BackPropagation: Novel Ideas for Training Neural Architectures, 2020.

Abstract | Links | BibTeX | Tags: deep learning, memory networks, recurrent neural network, Sequential data

Valenti, Andrea; Barsotti, Michele; Brondi, Raffaello; Bacciu, Davide; Ascari, Luca

ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs Conference

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, 2020.

Abstract | Links | BibTeX | Tags: autoencoder, biomedical data, deep learning, Sequential data

Bacciu, Davide; Errica, Federico; Micheli, Alessio; Podda, Marco

A Gentle Introduction to Deep Learning for Graphs Journal Article

Neural Networks, 129 , pp. 203-221, 2020.

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, structured data processing

Bacciu, Davide; Errica, Federico; Micheli, Alessio

Probabilistic Learning on Graphs via Contextual Architectures Journal Article

Journal of Machine Learning Research, 21 (134), pp. 1−39, 2020.

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

Castellana, Daniele; Bacciu, Davide

Generalising Recursive Neural Models by Tensor Decomposition Conference

Proceedings of the 2020 IEEE World Congress on Computational Intelligence, 2020.

Links | BibTeX | Tags: deep learning, structured data processing, tensor factorization, tensor neural networks, tree structured data

Cossu, Andrea; Carta, Antonio; Bacciu, Davide

Continual Learning with Gated Incremental Memories for Sequential Data Processing Conference

Proceedings of the 2020 IEEE World Congress on Computational Intelligence, 2020.

Links | BibTeX | Tags: Continual learning, deep learning, recurrent neural network, Sequential data

 Learning a Latent Space of Style-Aware Music Representations by Adversarial Autoencoders

Valenti, Andrea; Carta, Antonio; Bacciu, Davide

Learning a Latent Space of Style-Aware Music Representations by Adversarial Autoencoders Conference

Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), 2020.

Links | BibTeX | Tags: artificial creativity, autoencoder, deep learning, generative model, music generation

Carta, Antonio; Sperduti, Alessandro; Bacciu, Davide

Incremental training of a recurrent neural network exploiting a multi-scale dynamic memory Conference

Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020 (ECML-PKDD 2020), Springer International Publishing, 2020.

Abstract | BibTeX | Tags: autoencoder, deep learning, memory networks, recurrent neural network

A Fair Comparison of Graph Neural Networks for Graph Classification

Errica, Federico; Podda, Marco; Bacciu, Davide; Micheli, Alessio

A Fair Comparison of Graph Neural Networks for Graph Classification Conference

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

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, structured data processing

Tensor Decompositions in Deep Learning

Bacciu, Davide; Mandic, Danilo

Tensor Decompositions in Deep Learning Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.

Links | BibTeX | Tags: deep learning, structured data processing, tensor factorization

 Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data

Castellana, Daniele; Bacciu, Davide

Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.

Links | BibTeX | Tags: deep learning, structured data processing, tensor factorization, tree structured data

2019

Sequential Sentence Embeddings for Semantic Similarity

Bacciu, Davide; Carta, Antonio

Sequential Sentence Embeddings for Semantic Similarity Conference

Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI'19), IEEE, 2019.

Abstract | Links | BibTeX | Tags: autoencoder, deep learning, memory networks, natural language, recurrent neural network

A non-negative factorization approach to node pooling in graph convolutional neural networks

Bacciu, Davide; Di Sotto, Luigi

A non-negative factorization approach to node pooling in graph convolutional neural networks Conference

Proceedings of the 18th International Conference of the Italian Association for Artificial Intelligence (AIIA 2019), Lecture Notes in Artificial Intelligence Springer-Verlag, 2019.

Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

Bacciu, Davide; Carta, Antonio; Sperduti, Alessandro

Linear Memory Networks Conference

Proceedings of the 28th International Conference on Artificial Neural Networks (ICANN 2019), , 11727 , Lecture Notes in Computer Science Springer-Verlag, 2019.

Abstract | Links | BibTeX | Tags: autoencoder, deep learning, memory networks, recurrent neural network

Cosimo, Della Santina; Giuseppe, Averta; Visar, Arapi; Alessandro, Settimi; Giuseppe, Catalano Manuel; Davide, Bacciu; Antonio, Bicchi; Matteo, Bianchi

Autonomous Grasping with SoftHands: Combining Human Inspiration, Deep Learning and Embodied Machine Intelligence Presentation

11.09.2019.

BibTeX | Tags: deep learning, robotics

Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction

Crecchi, Francesco; Bacciu, Davide; Biggio, Battista

Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'19), i6doc.com, Louvain-la-Neuve, Belgium, 2019.

Links | BibTeX | Tags: adversarial attacks, deep learning, manifold learning

Societal Issues in Machine Learning: When Learning from Data is Not Enough

Bacciu, Davide; Biggio, Battista; Crecchi, Francesco; Lisboa, Paulo J G; Martin, José D; Oneto, Luca; Vellido, Alfredo

Societal Issues in Machine Learning: When Learning from Data is Not Enough Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'19), i6doc.com, Louvain-la-Neuve, Belgium, 2019.

Links | BibTeX | Tags: adversarial attacks, deep learning, explainable AI

Augmenting Recurrent Neural Networks Resilience by Dropout

Bacciu, Davide; Crecchi, Francesco

Augmenting Recurrent Neural Networks Resilience by Dropout Journal Article

IEEE Transactions on Neural Networs and Learning Systems, 2019.

Abstract | Links | BibTeX | Tags: ambient assisted living, deep learning, Echo state networks, recurrent neural network, reservoir computing

Learning from humans how to grasp: a data-driven architecture for autonomous grasping with anthropomorphic soft hands

Cosimo, Della Santina; Visar, Arapi; Giuseppe, Averta; Francesca, Damiani; Gaia, Fiore; Alessandro, Settimi; Giuseppe, Catalano Manuel; Davide, Bacciu; Antonio, Bicchi; Matteo, Bianchi

Learning from humans how to grasp: a data-driven architecture for autonomous grasping with anthropomorphic soft hands Journal Article

IEEE Robotics and Automation Letters, pp. 1-8, 2019, ISSN: 2377-3766, (Also accepted for presentation at ICRA 2019).

Links | BibTeX | Tags: convolutional neural network, deep learning, image understanding, machine vision, recurrent neural network, robotics

Deep Tree Transductions - A Short Survey

Davide, Bacciu; Antonio, Bruno

Deep Tree Transductions - A Short Survey Conference

Proceedings of the 2019 INNS Big Data and Deep Learning (INNSBDDL 2019) , Recent Advances in Big Data and Deep Learning Springer International Publishing, 2019.

Abstract | Links | BibTeX | Tags: deep learning, recurrent neural network, structured data processing, tree structured data

2018

Arapi, Visar; Santina, Cosimo Della; Bacciu, Davide; Bianchi, Matteo; Bicchi, Antonio

DeepDynamicHand: A deep neural architecture for labeling hand manipulation strategies in video sources exploiting temporal information Journal Article

Frontiers in Neurorobotics, 12 , pp. 86, 2018.

Abstract | Links | BibTeX | Tags: convolutional neural network, deep learning, image understanding, machine vision, recurrent neural network, robotics

Text Summarization as Tree Transduction by Top-Down TreeLSTM

Davide, Bacciu; Antonio, Bruno

Text Summarization as Tree Transduction by Top-Down TreeLSTM Conference

Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (SSCI'18), IEEE, 2018.

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, neural networks, structured data processing, tree structured data, tree transductions

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

Davide, Bacciu; Federico, Errica; Alessio, Micheli

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

Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 2018.

Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

Davide, Bacciu; Andrea, Bongiorno

Concentric ESN: Assessing the Effect of Modularity in Cycle Reservoirs Conference

Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN 2018) , IEEE, 2018.

Links | BibTeX | Tags: deep learning, Echo state networks, reservoir computing

Davide, Bacciu; JG, Lisboa Paulo; D, Martin Jose; Ruxandra, Stoean; Alfredo, Vellido

Bioinformatics and medicine in the era of deep learning Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'18), i6doc.com, Louvain-la-Neuve, Belgium, 2018, ISBN: 978-287587047-6.

Abstract | Links | BibTeX | Tags: bioinformatics, biomedical data, deep learning

2017

Davide, Bacciu

Hidden Tree Markov Networks: Deep and Wide Learning for Structured Data Conference

Proc. of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI'17), IEEE, 2017.

Links | BibTeX | Tags: deep learning, hidden tree Markov model, structured data processing

Davide, Bacciu; Francesco, Crecchi; Davide, Morelli

DropIn: Making Neural Networks Robust to Missing Inputs by Dropout Conference

Proceedings of the 2017 International Joint Conference on Neural Networks (IJCNN 2017) , IEEE, 2017, ISBN: 978-1-5090-6182-2.

Abstract | Links | BibTeX | Tags: ambient assisted living, deep learning, Echo state networks, recurrent neural network, reservoir computing

2016

Davide, Bacciu; Vincenzo, Gervasi; Giuseppe, Prencipe

An Investigation into Cybernetic Humor, or: Can Machines Laugh? Conference

Proceedings of the 8th International Conference on Fun with Algorithms (FUN'16) , 49 , Leibniz International Proceedings in Informatics (LIPIcs) Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2016, ISSN: 1868-8969.

Abstract | Links | BibTeX | Tags: deep learning, natural language, recurrent neural network, structured data processing