Publications

146 entries « 1 of 3 »

2021

Lanciano, Giacomo; Galli, Filippo; Cucinotta, Tommaso; Bacciu, Davide; Passarella, Andrea

Predictive Auto-scaling with OpenStack Monasca Conference Forthcoming

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2021), Forthcoming.

BibTeX | Tags: cloud computing, pervasive computing, recurrent neural network, Sequential data

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

Continual Learning with Echo State Networks Conference Forthcoming

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

BibTeX | Tags: Continual learning, Echo state networks, recurrent neural network, Sequential data

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

Dukic, Haris; Deligiorgis, Georgios; Sepe, Pierpaolo; Bacciu, Davide; Trincavelli, Marco

Inductive learning for product assortment graph completion Conference Forthcoming

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

BibTeX | Tags: deep learning for graphs, graph data, recommendation systems

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

Schoitsch, Erwin; Mylonas, Georgios (Ed.)

Supporting Privacy Preservation by Distributed and Federated Learning on the Edge Periodical

ERCIM News, 127 , 2021.

Links | BibTeX | Tags: artificial intelligence, Continual learning, edge AI, federated learning, humanistic intelligence, reservoir computing, trustworthy AI

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

K-Plex Cover Pooling for Graph Neural Networks Journal Article

In: 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

Macher, G.; Akarmazyan, S.; Armengaud, E.; Bacciu, D.; Calandra, C.; Danzinger, H.; Dazzi, P.; Davalas, C.; Gennaro, M. C. De; Dimitriou, A.; Dobaj, J.; Dzambic, M.; Giraudi, L.; Girbal, S.; Michail, D.; Peroglio, R.; Potenza, R.; Pourdanesh, F.; Seidl, M.; Sardianos, C.; Tserpes, K.; Valtl, J.; Varlamis, I.; Veledar, O.

Dependable Integration Concepts for Human-Centric AI-based Systems Workshop

Proceedings of the 40th International Conference on Computer Safety, Reliability and Security (SafeComp 2021), 2021, (Invited discussion paper).

BibTeX | Tags: dependable AI, humanistic intelligence, trustworthy AI

Macher, Georg; Armengaud, Eric; Bacciu, Davide; Dobaj, Jürgen; Dzambic, Maid; Seidl, Matthias; Veledar, Omar

Dependable Integration Concepts for Human-Centric AI-based Systems Workshop

Proceedings of the 16th International Workshop on Dependable Smart Embedded Cyber-Physical Systems and Systems-of-Systems (DECSoS 2021), 2021.

Abstract | BibTeX | Tags: dependable AI, humanistic intelligence, trustworthy AI

Resta, Michele; Monreale, Anna; Bacciu, Davide

Occlusion-based Explanations in Deep Recurrent Models for Biomedical Signals Journal Article Forthcoming

In: Entropy, Forthcoming, (Special issue on Representation Learning).

Abstract | BibTeX | Tags: biomedical data, explainable AI, recurrent neural network, Sequential data

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

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

In: Neural Networks, Forthcoming.

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

Bacciu, Davide; Akarmazyan, Siranush; Armengaud, Eric; Bacco, Manlio; Bravos, George; Calandra, Calogero; Carlini, Emanuele; Carta, Antonio; Cassara, Pietro; Coppola, Massimo; Davalas, Charalampos; Dazzi, Patrizio; Degennaro, Maria Carmela; Sarli, Daniele Di; Dobaj, Jürgen; Gallicchio, Claudio; Girbal, Sylvain; Gotta, Alberto; Groppo, Riccardo; Lomonaco, Vincenzo; Macher, Georg; Mazzei, Daniele; Mencagli, Gabriele; Michail, Dimitrios; Micheli, Alessio; Peroglio, Roberta; Petroni, Salvatore; Potenza, Rosaria; Pourdanesh, Farank; Sardianos, Christos; Tserpes, Konstantinos; Tagliabò, Fulvio; Valtl, Jakob; Varlamis, Iraklis; Veledar, Omar (Ed.)

TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence Conference Forthcoming

Proceedings of the 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS) , Forthcoming.

BibTeX | Tags: artificial intelligence, Continual learning, federated learning, humanistic intelligence, reservoir computing, trustworthy AI

Antonio Carta Andrea Rosasco, Andrea Cossu

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

Atzeni, Daniele; Bacciu, Davide; Errica, Federico; Micheli, Alessio

Modeling Edge Features with Deep Bayesian Graph Networks Conference Forthcoming

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

BibTeX | Tags: deep learning for graphs, generative model, hidden Markov models, structured data processing

Numeroso, Danilo; Bacciu, Davide

MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks Conference Forthcoming

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

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

Bacciu, Davide; Sarli, Daniele Di; Faraji, Pouria; Gallicchio, Claudio; Micheli, Alessio

Federated Reservoir Computing Neural Networks Conference Forthcoming

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

BibTeX | Tags: activity recognition, distributed learning, Echo state networks, federated learning, internet of things, pervasive computing, randomized networks, reservoir computing, Sequential data

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

Errica, Federico; Bacciu, Davide; Micheli, Alessio

Graph Mixture Density Networks Conference Forthcoming

Proceedings of the 38th International Conference on Machine Learning (ICML 2021), Forthcoming.

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

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

Sattar, Asma; Bacciu, Davide

Context-aware Graph Convolutional Autoencoder Conference Forthcoming

Proceedings of the 16th International Work Conference on Artificial Neural Networks (IWANN 2021), Forthcoming.

BibTeX | Tags: deep learning for graphs, graph data, recommendation systems

Bacciu, Davide; Sarli, Daniele Di; Gallicchio, Claudio; Micheli, Alessio; Puccinelli, Niccolo

Benchmarking Reservoir and Recurrent Neural Networks for Human State and Activity Recognition Conference Forthcoming

Proceedings of the 16th International Work Conference on Artificial Neural Networks (IWANN 2021), Forthcoming.

BibTeX | Tags: activity recognition, Echo state networks, recurrent neural network, reservoir computing

Castellana, Daniele; Bacciu, Davide

A Tensor Framework for Learning in Structured Domains Journal Article Forthcoming

In: 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

In: Neurocomputing, 2021.

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

Carta, Antonio; Cossu, Andrea; Errica, Federico; Bacciu, Davide

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

The Web Conference 2021 Workshop on Graph Learning Benchmarks (GLB21), 2021.

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

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

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

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

Bontempi, Gianluca; Chavarriaga, Ricardo; Canck, Hans De; Girardi, Emanuela; Hoos, Holger; Kilbane-Dawe, Iarla; Ball, Tonio; Nowé, Ann; Sousa, Jose; Bacciu, Davide; Aldinucci, Marco; Domenico, Manlio De; Saffiotti, Alessandro; Maratea, Marco

The CLAIRE COVID-19 initiative: approach, experiences and recommendations Journal Article

In: Ethics and Information Technology, 2021.

Links | BibTeX | Tags: artificial intelligence, bioinformatics, biomedical data

Michele Barsotti Andrea Valenti, Davide Bacciu; Ascari, Luca

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

In: Bioengineering , 2021.

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

Bacciu, Davide; Bertoncini, Gioele; Morelli, Davide

Topographic mapping for quality inspection and intelligent filtering of smart-bracelet data Journal Article

In: Neural Computing Applications, 2021.

Links | BibTeX | Tags: biomedical data, data visualization, explainable AI, internet of things, multivariate time-series, self-organizing map

Crecchi, Francesco; Melis, Marco; Sotgiu, Angelo; Bacciu, Davide; Biggio, Battista

FADER: Fast Adversarial Example Rejection Journal Article

In: Neurocomputing, 2021, ISSN: 0925-2312.

Links | BibTeX | Tags: adversarial examples, adversarial machine learning, deep learning, detection, evasion attacks, rbf networks

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

Bacciu, Davide; Numeroso, Danilo

Explaining Deep Graph Networks with Molecular Counterfactuals Workshop

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Workshop on Machine Learning for Molecules - Accepted as Contributed Talk (Oral), 2020.

Abstract | Links | BibTeX | Tags: deep learning for graphs, explainable AI, graph data, 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

Castellana, Daniele; Bacciu, Davide

Learning from Non-Binary Constituency Trees via Tensor Decomposition Conference

PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS (COLING 2020), 2020.

BibTeX | Tags: natural language processing, tensor factorization, tensor neural networks, tree structured 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

In: 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

In: 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 Deep Generative Model for Fragment-Based Molecule Generation

Podda, Marco; Bacciu, Davide; Micheli, Alessio

A Deep Generative Model for Fragment-Based Molecule Generation Conference

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020) , 2020.

Abstract | Links | BibTeX | Tags: deep learning for graphs, generative model, graph data, molecule generation, recurrent neural network, structured data processing

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

 Biochemical Pathway Robustness Prediction with Graph Neural Networks

Podda, Marco; Micheli, Alessio; Bacciu, Davide; Milazzo, Paolo

Biochemical Pathway Robustness Prediction with Graph Neural Networks Conference

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

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

 Theoretically Expressive and Edge-aware Graph Learning

Errica, Federico; Bacciu, Davide; Micheli, Alessio

Theoretically Expressive and Edge-aware Graph Learning Conference

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

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

 Perplexity-free Parametric t-SNE

Crecchi, Francesco; de Bodt, Cyril; Bacciu, Davide; Verleysen, Michel; John, Lee

Perplexity-free Parametric t-SNE Conference

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

BibTeX | Tags: data visualization, manifold learning, neural networks, unsupervised learning

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

Deep Learning for Graphs

Bacciu, Davide; Micheli, Alessio

Deep Learning for Graphs Book Chapter

In: Oneto, Luca; Navarin, Nicolo; Sperduti, Alessandro; Anguita, Davide (Ed.): Recent Trends in Learning From Data: Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019), 896 , pp. 99-127, Springer International Publishing, 2020, ISBN: 978-3-030-43883-8.

Abstract | Links | BibTeX | Tags: deep learning for graphs, generative model, graph data, molecule generation, recurrent neural network, structured data processing

Measuring the effects of confounders in medical supervised classification problems: the Confounding Index (CI)

Ferrari, Elisa; Retico, Alessandra; Bacciu, Davide

Measuring the effects of confounders in medical supervised classification problems: the Confounding Index (CI) Journal Article

In: Artificial Intelligence in Medicine, 103 , 2020.

Abstract | Links | BibTeX | Tags: artificial intelligence, bioinformatics, biomedical data, explainable AI, statistics

146 entries « 1 of 3 »