Publications

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2021

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

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

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

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

 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

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

Deep Learning for Graphs

Bacciu, Davide; Micheli, Alessio

Deep Learning for Graphs Book Chapter

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

2019

Edge-based sequential graph generation with recurrent neural networks

Bacciu, Davide; Micheli, Alessio; Podda, Marco

Edge-based sequential graph generation with recurrent neural networks Journal Article

Neurocomputing, 2019.

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

Graph generation by sequential edge prediction

Bacciu, Davide; Micheli, Alessio; Podda, Marco

Graph generation by sequential edge prediction 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: deep learning for graphs, generative model, graph data, structured data processing

2015

Davide, Bacciu; J.G., Lisboa Paulo; Alessandro, Sperduti; Thomas, Villmann

Probabilistic Modeling in Machine Learning Incollection

Kacprzyk, Janusz ; Pedrycz, Witold (Ed.): pp. 545–575, Springer Berlin Heidelberg, Berlin, Heidelberg, 2015, ISBN: 978-3-662-43505-2.

Links | BibTeX | Tags: Bayesian networks, generative model, graphical models, hidden Markov models

2014

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Integrating bi-directional contexts in a generative kernel for trees Conference

Neural Networks (IJCNN), 2014 International Joint Conference on, IEEE, 2014.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data, tree transductions

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Modeling Bi-directional Tree Contexts by Generative Transductions Conference

Neural Information Processing, 8834 , Springer International Publishing, 2014.

Abstract | Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, tree kernel, tree structured data

2012

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

A Generative Multiset Kernel for Structured Data Conference

Artificial Neural Networks and Machine Learning - ICANN 2012 proceedings, Springer LNCS series, 7552 , Springer-Verlag, BERLIN HEIDELBERG, 2012.

Abstract | Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, structured data processing, support vector machine, tree kernel, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Input-Output Hidden Markov Models for Trees Conference

ESANN 2012 - The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings, Ciaco scrl - i6doc.com, 2012.

Abstract | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data, tree transductions

2011

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Adaptive Tree Kernel by Multinomial Generative Topographic Mapping Conference

Proceedings of the International Joint Conference on Neural Networks, IEEE, Piscataway (NJ), 2011.

Links | BibTeX | Tags: generative model, generative topographic mapping, graphical models, hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data

2010

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

A Bottom-up Hidden Tree Markov Model Technical Report

Università di Pisa (TR-10-08), 2010.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Bottom-Up Generative Modeling of Tree-Structured Data Conference

LNCS 6443: Neural Information Processing. Theory and Algorithms. Part I, 6443 , Springer-Verlag, BERLIN HEIDELBERG, 2010.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data

2009

Davide, Bacciu; H, Jarman Ian; A, Etchells Terence; G, Lisboa Paulo J

Patient stratification with competing risks by multivariate Fisher distance Conference

2009 International Joint Conference on Neural Networks, IEEE, 2009.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, generative model, neural networks, statistics, survival analysis, unsupervised learning

2008

Davide, Bacciu

A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections PhD Thesis

2008.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, feature selection, generative model, graphical models, image understanding, latent topic model, neural networks, statistics, unsupervised learning