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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

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

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

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

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; 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

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

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

2020

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

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

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

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

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

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

Castellana, Daniele; Bacciu, Davide

Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models Conference

Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN 2019I) , IEEE, 2019.

Abstract | Links | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data; tensor factorization; Bayesian learning

Bayesian Mixtures of Hidden Tree Markov Models for Structured Data Clustering

Davide, Bacciu; Daniele, Castellana

Bayesian Mixtures of Hidden Tree Markov Models for Structured Data Clustering Journal Article

Neurocomputing, 342 , pp. 49-59, 2019, ISBN: 0925-2312.

Abstract | Links | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data, unsupervised learning

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

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

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

Davide, Bacciu; Daniele, Castellana

Learning Tree Distributions by Hidden Markov Models Workshop

Proceedings of the FLOC 2018 Workshop on Learning and Automata (LearnAut'18), 2018.

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

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; Daniele, Castellana

Mixture of Hidden Markov Models as Tree Encoder 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 | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data, unsupervised learning

Generative Kernels for Tree-Structured Data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Generative Kernels for Tree-Structured Data Journal Article

Neural Networks and Learning Systems, IEEE Transactions on, 2018, ISSN: 2162-2388 .

Abstract | Links | BibTeX | Tags: hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data

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

2016

Davide, Bacciu

Unsupervised feature selection for sensor time-series in pervasive computing applications Journal Article

Neural Computing and Applications, 27 (5), pp. 1077-1091, 2016, ISSN: 1433-3058.

Abstract | Links | BibTeX | Tags: ambient assisted living, Echo state networks, feature selection, multivariate time-series, pervasive computing, structured data processing, wireless sensor networks

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

Giuseppe, Amato; Davide, Bacciu; Stefano, Chessa; Mauro, Dragone; Claudio, Gallicchio; Claudio, Gennaro; Hector, Lozano; Alessio, Micheli; Arantxa, Renteria; Claudio, Vairo

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living Conference

Proceedings of the 7th International Conference on Ambient Intelligence (ISAMI'16), 476 , Advances in Intelligent Systems and Computing Springer, 2016, ISBN: 978-3-319-40113-3.

Abstract | Links | BibTeX | Tags: activity recognition, ambient assisted living, cognitive robotics, Echo state networks, multivariate time-series, robotic ecology, structured data processing, wireless sensor networks

Davide, Bacciu; Claudio, Gallicchio; Alessio, Micheli

A reservoir activation kernel for trees Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'16), i6doc.com, 2016, ISBN: 978-287587027-.

Links | BibTeX | Tags: Echo state networks, kernel methods, reservoir computing, structured data processing, tree kernel, tree structured data

2015

Davide, Bacciu; Filippo, Benedetti; Alessio, Micheli

ESNigma: efficient feature selection for Echo State Networks Conference

Proceedings of the 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'15), i6doc.com publ., 2015.

Abstract | Links | BibTeX | Tags: Echo state networks, feature selection, multivariate time-series, pervasive computing, reservoir computing, structured data processing, wireless sensor networks

Giuseppe, Amato; Davide, Bacciu; Mathias, Broxvall; Stefano, Chessa; Sonya, Coleman; Maurizio, Di Rocco; Mauro, Dragone; Claudio, Gallicchio; Claudio, Gennaro; Hector, Lozano; Martin, McGinnity T; Alessio, Micheli; AK, Ray; Arantxa, Renteria; Alessandro, Saffiotti; David, Swords; Claudio, Vairo; Philip, Vance

Robotic Ubiquitous Cognitive Ecology for Smart Homes Journal Article

Journal of Intelligent & Robotic Systems, 80 (1), pp. 57-81, 2015, ISSN: 0921-0296.

Abstract | Links | BibTeX | Tags: activity recognition, ambient assisted living, cognitive robotics, Echo state networks, multivariate time-series, networked robotics, pervasive computing, planning, reservoir computing, robotic ecology, structured data processing, wireless sensor networks

2014

Davide, Bacciu

An Iterative Feature Filter for Sensor Timeseries in Pervasive Computing Applications Conference

Communications in Computer and Information ScienceEngineering Applications of Neural Networks, 459 , Springer International Publishing, 2014.

Abstract | Links | BibTeX | Tags: ambient assisted living, feature selection, multivariate time-series, pervasive computing, structured data processing, unsupervised learning, wireless sensor networks

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

2013

An input–output hidden Markov model for tree transductions

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

An input–output hidden Markov model for tree transductions Journal Article

Neurocomputing, 112 , pp. 34–46, 2013, ISSN: 0925-2312.

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

Davide, Bacciu; Stefano, CHESSA; Claudio, Gallicchio; Alessio, MICHELI; Paolo, Barsocchi

An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living Conference

Neural Nets and Surroundings - 22nd Italian Workshop on Neural Nets, 19 , Springer, 2013.

Links | BibTeX | Tags: Echo state networks, indoor user movement forecasting, pervasive computing, recurrent neural network, reservoir computing, structured data processing, wireless sensor networks

Nicola, Di Mauro; Paolo, Frasconi; Fabrizio, Angiulli; Davide, Bacciu; de Marco, Gemmis; Floriana, Esposito; Nicola, Fanizzi; Stefano, Ferilli; Marco, Gori; A, Lisi Francesca; others,

Italian Machine Learning and Data Mining research: The last years Journal Article

Intelligenza Artificiale, 7 (2), pp. 77–89, 2013.

Links | BibTeX | Tags: graphical models, recurrent neural network, structured data processing

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

Davide, Bacciu; Claudio, Gallicchio; Alessio, Micheli; Paolo, Barsocchi; Stefano, Chessa

Predicting User Movements in Heterogeneous Indoor Environments by Reservoir Computing Conference

Proceedings of the IJCAI Workshop on Space, Time and Ambient Intelligence (STAMI), 2011.

Links | BibTeX | Tags: activity recognition, ambient assisted living, Echo state networks, indoor user movement forecasting, multivariate time-series, pervasive computing, recurrent neural network, reservoir computing, structured data processing, wireless sensor networks

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

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Compositional Generative Mapping of Structured Data Conference

Proceedings of the 2010 IEEE InternationalJoint Conference on Neural Networks(IJCNN'10), IEEE, 2010.

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

52 entries « 1 of 2 »