Alessio Micheli

Orcid: 0000-0001-5764-5238

According to our database1, Alessio Micheli authored at least 171 papers between 2000 and 2024.

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Bibliography

2024
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Designs of graph echo state networks for node classification.
Neurocomputing, 2024

Investigating over-parameterized randomized graph networks.
Neurocomputing, 2024

Antibody design using deep learning: from sequence and structure design to affinity maturation.
Briefings Bioinform., 2024

Explaining Graph Classifiers by Unsupervised Node Relevance Attribution.
Proceedings of the Explainable Artificial Intelligence, 2024

Continuously Deep Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Multitarget Wastewater Quality Assessment in a Smart Industry Context.
Proceedings of the International Conference on Intelligent Environments, 2024

Onion Echo State Networks - A Preliminary Analysis of Dynamics.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Hybrid CNN-MLP for Wastewater Quality Estimation.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023
Architectural richness in deep reservoir computing.
Neural Comput. Appl., December, 2023

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs.
J. Open Source Softw., October, 2023

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs.
Bioinform., October, 2023

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs.
Dataset, October, 2023

Guest Editorial: Trends in Reservoir Computing.
Cogn. Comput., September, 2023

Biochemical networks with simulation-based estimations of dynamical properties.
Dataset, June, 2023

Addressing heterophily in node classification with graph echo state networks.
Neurocomputing, 2023

Is Rewiring Actually Helpful in Graph Neural Networks?
CoRR, 2023

Analysis and Interpretation of ECG Time Series Through Convolutional Neural Networks in Brugada Syndrome Diagnosis.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Minimum Spanning Set Selection in Graph Kernels.
Proceedings of the Graph-Based Representations in Pattern Recognition, 2023

Richness of Node Embeddings in Graph Echo State Networks.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Entropy Based Regularization Improves Performance in the Forward-Forward Algorithm.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Hidden Markov Models for Temporal Graph Representation Learning.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Graph Representation Learning.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022
Guest Editorial Special Issue on New Frontiers in Extremely Efficient Reservoir Computing.
IEEE Trans. Neural Networks Learn. Syst., 2022

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview.
Neurocomputing, 2022

Discrete-time dynamic graph echo state networks.
Neurocomputing, 2022

Pyramidal Reservoir Graph Neural Network.
Neurocomputing, 2022

Leave Graphs Alone: Addressing Over-Squashing without Rewiring.
CoRR, 2022

On the effectiveness of Gated Echo State Networks for data exhibiting long-term dependencies.
Comput. Sci. Inf. Syst., 2022

Spectral Bounds for Graph Echo State Network Stability.
Proceedings of the International Joint Conference on Neural Networks, 2022

The Infinite Contextual Graph Markov Model.
Proceedings of the International Conference on Machine Learning, 2022

Hierarchical Dynamics in Deep Echo State Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Beyond Homophily with Graph Echo State Networks.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

Input Routed Echo State Networks.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
Deep Reservoir Computing.
Proceedings of the Reservoir Computing, 2021

A preliminary evaluation of Echo State Networks for Brugada syndrome classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Benchmarking Reservoir and Recurrent Neural Networks for Human State and Activity Recognition.
Proceedings of the Advances in Computational Intelligence, 2021

Phase Transition Adaptation.
Proceedings of the International Joint Conference on Neural Networks, 2021

Federated Reservoir Computing Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021

Modeling Edge Features with Deep Bayesian Graph Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021

Graph Mixture Density Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Dynamic Graph Echo State Networks.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Complex Data: Learning Trustworthily, Automatically, and with Guarantees.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Robust Malware Classification via Deep Graph Networks on Call Graph Topologies.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021


2020
Hierarchical Temporal Representation in Linear Reservoir Computing.
Proceedings of the Neural Advances in Processing Nonlinear Dynamic Signals, 2020

EchoBay: Design and Optimization of Echo State Networks under Memory and Time Constraints.
ACM Trans. Archit. Code Optim., 2020

A gentle introduction to deep learning for graphs.
Neural Networks, 2020

Probabilistic Learning on Graphs via Contextual Architectures.
J. Mach. Learn. Res., 2020

Edge-based sequential graph generation with recurrent neural networks.
Neurocomputing, 2020

Text classification by untrained sentence embeddings.
Intelligenza Artificiale, 2020

Accelerating the identification of informative reduced representations of proteins with deep learning for graphs.
CoRR, 2020

Machine learning approaches for identifying prey handling activity in otariid pinnipeds.
CoRR, 2020

Gated Echo State Networks: a preliminary study.
Proceedings of the International Conference on INnovations in Intelligent SysTems and Applications, 2020

Ring Reservoir Neural Networks for Graphs.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

A Fair Comparison of Graph Neural Networks for Graph Classification.
Proceedings of the 8th International Conference on Learning Representations, 2020

A Preliminary Investigation of Machine Learning Approaches for Mobility Monitoring from Smartphone Data.
Proceedings of the Computational Science and Its Applications - ICCSA 2020, 2020

Time Series Clustering with Deep Reservoir Computing.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Biochemical Pathway Robustness Prediction with Graph Neural Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Simplifying Deep Reservoir Architectures.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Theoretically Expressive and Edge-aware Graph Learning.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Pyramidal Graph Echo State Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Efficient Embedded Machine Learning applications using Echo State Networks.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Classification of Biochemical Pathway Robustness with Neural Networks for Graphs.
Proceedings of the Biomedical Engineering Systems and Technologies, 2020

Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks.
Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020), 2020

A Deep Generative Model for Fragment-Based Molecule Generation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Fast and Deep Graph Neural Networks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Editorial: Booming of Neural Networks and Learning Systems.
IEEE Trans. Neural Networks Learn. Syst., 2019

Deep Reservoir Neural Networks for Trees.
Inf. Sci., 2019

An ambient intelligence approach for learning in smart robotic environments.
Comput. Intell., 2019

Richness of Deep Echo State Network Dynamics.
Proceedings of the Advances in Computational Intelligence, 2019

Fast Spectral Radius Initialization for Recurrent Neural Networks.
Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Deep Learning for Graphs.
Proceedings of the Recent Trends in Learning From Data, 2019

Reservoir Topology in Deep Echo State Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Continuous Blood Pressure Estimation Through Optimized Echo State Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Embeddings and Representation Learning for Structured Data.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Comparison between DeepESNs and gated RNNs on multivariate time-series prediction.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Graph generation by sequential edge prediction.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Question Classification with Untrained Recurrent Embeddings.
Proceedings of the AI*IA 2019 - Advances in Artificial Intelligence, 2019

2018
Generative Kernels for Tree-Structured Data.
IEEE Trans. Neural Networks Learn. Syst., 2018

Design of deep echo state networks.
Neural Networks, 2018

Local Lyapunov exponents of deep echo state networks.
Neurocomputing, 2018

Deep Tree Echo State Networks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Why Layering in Recurrent Neural Networks? A DeepESN Survey.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Tree Edit Distance Learning via Adaptive Symbol Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing.
Proceedings of the 35th International Conference on Machine Learning, 2018

Combining Memory and Non-linearity in Echo State Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

ITAmoji 2018: Emoji Prediction via Tree Echo State Networks.
Proceedings of the Sixth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2018) co-located with the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018), 2018

Randomized Recurrent Neural Networks.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Deep Echo State Networks for Diagnosis of Parkinson's Disease.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Reliability and human factors in Ambient Assisted Living environments - The DOREMI case study.
J. Reliab. Intell. Environ., 2017

Deep reservoir computing: A critical experimental analysis.
Neurocomputing, 2017

A learning system for automatic Berg Balance Scale score estimation.
Eng. Appl. Artif. Intell., 2017

Deep Echo State Network (DeepESN): A Brief Survey.
CoRR, 2017

Hierarchical Temporal Representation in Linear Reservoir Computing.
CoRR, 2017

Echo State Property of Deep Reservoir Computing Networks.
Cogn. Comput., 2017

A Comparative Analysis of SVM and IDNN for Identifying Penguin Activities.
Appl. Artif. Intell., 2017

On the need of machine learning as a service for the internet of things.
Proceedings of the 1st International Conference on Internet of Things and Machine Learning, 2017

Local Lyapunov Exponents of Deep RNN.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Randomized Machine Learning Approaches: Recent Developments and Challenges.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Experimental Analysis of Deep Echo State Networks for Ambient Assisted Living.
Proceedings of the Third Italian Workshop on Artificial Intelligence for Ambient Assisted Living 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017

2016
Activity Recognition system based on Multisensor data fusion (AReM).
Dataset, May, 2016

Indoor User Movement Prediction from RSS data.
Dataset, February, 2016

Human activity recognition using multisensor data fusion based on Reservoir Computing.
J. Ambient Intell. Smart Environ., 2016

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living.
Proceedings of the Ambient Intelligence - Software and Applications, 2016

Detecting Socialization Events in Ageing People: The Experience of the DOREMI Project.
Proceedings of the 12th International Conference on Intelligent Environments, 2016

Deep Reservoir Computing: A Critical Analysis.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

RSS-based Robot Localization in Critical Environments using Reservoir Computing.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

A reservoir activation kernel for trees.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

A Reservoir Computing Approach for Human Gesture Recognition from Kinect Data.
Proceedings of the Artificial Intelligence for Ambient Assisted Living 2016 co-located with 15th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2016), 2016

2015
Robotic Ubiquitous Cognitive Ecology for Smart Homes.
J. Intell. Robotic Syst., 2015

Prediction of the Italian electricity price for smart grid applications.
Neurocomputing, 2015

A cognitive robotic ecology approach to self-configuring and evolving AAL systems.
Eng. Appl. Artif. Intell., 2015

Preliminary Experimental Analysis of Reservoir Computing Approach for Balance Assessment.
Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, 2015

A Reservoir Computing Approach for Balance Assessment.
Proceedings of the Advanced Analysis and Learning on Temporal Data, 2015

Structured parallel implementation of Tree Echo State Network model selection.
Proceedings of the Parallel Computing: On the Road to Exascale, 2015

ESNigma: efficient feature selection for echo state networks.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Smart Environments and Context-Awareness for Lifestyle Management in a Healthy Active Ageing Framework.
Proceedings of the Progress in Artificial Intelligence, 2015

2014
An experimental characterization of reservoir computing in ambient assisted living applications.
Neural Comput. Appl., 2014

Integrating bi-directional contexts in a generative kernel for trees.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Learning context-aware mobile robot navigation in home environments.
Proceedings of the 5th International Conference on Information, 2014

Modeling Bi-directional Tree Contexts by Generative Transductions.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

2013
Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model.
IEEE Trans. Neural Networks Learn. Syst., 2013

Novel approaches in machine learning and computational intelligence.
Neurocomputing, 2013

Tree Echo State Networks.
Neurocomputing, 2013

An input-output hidden Markov model for tree transductions.
Neurocomputing, 2013

Forecast-Driven Enhancement of Received Signal Strength (RSS)-Based Localization Systems.
ISPRS Int. J. Geo Inf., 2013

Italian Machine Learning and Data Mining research: The last years.
Intelligenza Artificiale, 2013

Robot Localization by Echo State Networks Using RSS.
Proceedings of the Recent Advances of Neural Network Models and Applications, 2013

Distributed Neural Computation over WSN in Ambient Intelligence.
Proceedings of the Ambient Intelligence - Software and Applications, 2013

Multisensor Data Fusion for Activity Recognition Based on Reservoir Computing.
Proceedings of the Evaluating AAL Systems Through Competitive Benchmarking, 2013

2012
Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees.
IEEE Trans. Neural Networks Learn. Syst., 2012

An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living.
Proceedings of the Neural Nets and Surroundings - 22nd Italian Workshop on Neural Nets, 2012

A General Purpose Distributed Learning Model for Robotic Ecologies.
Proceedings of the 10th IFAC Symposium on Robot Control, SyRoCo 2012, Dubrovnik, Croatia, 2012

Robotic UBIquitous COgnitive Network.
Proceedings of the Ambient Intelligence - Software and Applications, 2012

A Generative Multiset Kernel for Structured Data.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Constructive Reservoir Computation with Output Feedbacks for Structured Domains.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Input-Output Hidden Markov Models for trees.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
Architectural and Markovian factors of echo state networks.
Neural Networks, 2011

Supervised State Mapping of Clustered GraphESN States.
Proceedings of the Neural Nets WIRN11, 2011

User Movements Forecasting by Reservoir Computing Using Signal Streams Produced by Mote-Class Sensors.
Proceedings of the Mobile Lightweight Wireless Systems, 2011

Adaptive tree kernel by multinomial generative topographic mapping.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Exploiting vertices states in GraphESN by weighted nearest neighbor.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

2010
Graph Echo State Networks.
Proceedings of the International Joint Conference on Neural Networks, 2010

Compositional generative mapping of structured data.
Proceedings of the International Joint Conference on Neural Networks, 2010

Bottom-Up Generative Modeling of Tree-Structured Data.
Proceedings of the Neural Information Processing. Theory and Algorithms, 2010

TreeESN: a Preliminary Experimental Analysis.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

A Markovian characterization of redundancy in echo state networks by PCA.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2009
Recursive Neural Networks for Cheminformatics: QSPR for Polymeric Compounds (Towards Biomaterials Design).
Proceedings of the Computational Intelligence and Bioengineering, 2009

Neural Network for Graphs: A Contextual Constructive Approach.
IEEE Trans. Neural Networks, 2009

Modeling adaptive kernels from probabilistic phylogenetic trees.
Artif. Intell. Medicine, 2009

2007
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties.
Proceedings of the Perspectives of Neural-Symbolic Integration, 2007

Generative Kernels for Gene Function Prediction Through Probabilistic Tree Models of Evolution.
Proceedings of the Applications of Fuzzy Sets Theory, 2007

Recursive Principal Component Analysis of Graphs.
Proceedings of the Artificial Neural Networks, 2007

A general framework for unsupervised preocessing of structured data.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2006
Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks.
J. Chem. Inf. Model., 2006

2005
Universal Approximation Capability of Cascade Correlation for Structures.
Neural Comput., 2005

A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains.
Neurocomputing, 2005

A New Neural Network Model for Contextual Processing of Graphs.
Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005

2004
Contextual processing of structured data by recursive cascade correlation.
IEEE Trans. Neural Networks, 2004

Recursive self-organizing network models.
Neural Networks, 2004

A general framework for unsupervised processing of structured data.
Neurocomputing, 2004

A Preliminary Investigation on Connecting Genotype to Oral Cancer Development through XCS.
Proceedings of the Biological and Artificial Intelligence Environments, 2004

A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

2003
QSAR/QSPR Studies by Kernel Machines, Recursive Neural Networks and Their Integration.
Proceedings of the Neural Nets, 14th Italian Workshop on Neural Nets, 2003

Formal Determination of Context in Contextual Recursive Cascade Correlation Networks.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

2002
A general framework for unsupervised processing of structured data.
Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

2001
Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure-Activity Relationship Studies of Benzodiazepines.
J. Chem. Inf. Comput. Sci., 2001

2000
Application of Cascade Correlation Networks for Structures to Chemistry.
Appl. Intell., 2000

Building MLP Networks by Construction.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Bi-Causal Recurrent Cascade Correlation.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000


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