F. Scarselli

发表

On the complexity of shallow and deep neural network classifiers

Franco Scarselli, Monica Bianchini, M. Bianchini, 2014, ESANN.

The Graph Neural Network Model

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2009, IEEE Transactions on Neural Networks.

Adaptive ranking of web pages

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2003, WWW '03.

On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures

Franco Scarselli, Monica Bianchini, M. Bianchini, 2014, IEEE Transactions on Neural Networks and Learning Systems.

A new model for learning in graph domains

F. Scarselli, M. Gori, G. Monfardini, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Graph neural networks for ranking Web pages

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2005, The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05).

Are Multilayer Perceptrons Adequate for Pattern Recognition and Verification?

Franco Scarselli, Marco Gori, F. Scarselli, 1998, IEEE Trans. Pattern Anal. Mach. Intell..

XML Document Mining Using Contextual Self-organizing Maps for Structures

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2006, INEX.

Computational Capabilities of Graph Neural Networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2009, IEEE Transactions on Neural Networks.

Clustering XML Documents Using Self-organizing Maps for Structures

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2005, INEX.

A Simple Focused Crawler

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2003, The Web Conference.

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

A. Mecocci, A. Lallas, G. Argenziano, 2020, Journal of dermatological science.

An introduction to learning in web domains

Ah Chung Tsoi, Franco Scarselli, Marco Gori, 2003, ESANN.

Segmentation of Petri Plate Images for Automatic Reporting of Urine Culture Tests

A. Mecocci, M. Bianchini, F. Scarselli, 2021, Handbook of Artificial Intelligence in Healthcare.

Deep Learning Approaches for the Segmentation of Glomeruli in Kidney Histopathological Images

Giovanna Maria Dimitri, A. Mecocci, M. Bianchini, 2022, Mathematics.

Robust Prostate Cancer Classification with Siamese Neural Networks

Franco Scarselli, Monica Bianchini, Alberto Rossi, 2020, ISVC.

Investigation into the application of graph neural networks to large-scale recommender systems

Franco Scarselli, Markus Hagenbuchner, Marco Gori, 2006 .

Neurocomputing - Special Issue on Pattern Recognition in Graphical Domains

Franco Scarselli, Monica Bianchini, M. Bianchini, 2009 .

Deep Learning Techniques for Dragonfly Action Recognition

Franco Scarselli, Monica Bianchini, Alberto Rossi, 2020, ICPRAM.

Molecular generative Graph Neural Networks for Drug Discovery

Franco Scarselli, Monica Bianchini, Pietro Bongini, 2020, Neurocomputing.

A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation pdf

Franco Scarselli, Alessandro Mecocci, Monica Bianchini, 2019, ArXiv.

Searching the Web: learning based techniques

Franco Scarselli, Marco Gori, Marco Maggini, 2001, The European Symposium on Artificial Neural Networks.

Recursive networks for processing graphs with labelled edges

Franco Scarselli, Marco Maggini, Monica Bianchini, 2004, The European Symposium on Artificial Neural Networks.

PageRank: A Circuital Analysis

Franco Scarselli, Marco Gori, Monica Bianchini, 2002 .

Complex Data: Learning Trustworthily, Automatically, and with Guarantees

Alessio Micheli, Franco Scarselli, Alessandro Sperduti, 2021, ESANN.

A unifying point of view on expressive power of GNNs

M. Bianchini, F. Scarselli, M. Sampoli, 2021, ArXiv.

Research Online Research Online The graph neural network model The graph neural network model

A. Tsoi, F. Scarselli, M. Gori, 2022 .

Drug Side Effect Prediction with Deep Learning Molecular Embedding in a Graph-of-Graphs Domain

F. Scarselli, P. Bongini, Niccolò Pancino, 2022, Mathematics.

On Inductive–Transductive Learning With Graph Neural Networks

M. Bianchini, F. Scarselli, Alberto Rossi, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

M. Bianchini, F. Scarselli, A. Micheli, 2022, Neurocomputing.

A fully recursive perceptron network architecture

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

Franco Scarselli, Monica Bianchini, M. Bianchini, 2009, Multimedia Techniques for Device and Ambient Intelligence.

Neural networks for relational learning: an experimental comparison

Franco Scarselli, Marco Gori, Hendrik Blockeel, 2011, Machine Learning.

Analysis of brain NMR images for age estimation with deep learning

Franco Scarselli, Monica Bianchini, Alberto Rossi, 2019, KES.

A Comparison between Recursive Neural Networks and Graph Neural Networks

Franco Scarselli, Marco Gori, Marco Maggini, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Graph Neural Networks for Object Localization

Franco Scarselli, Marco Gori, Vincenzo Di Massa, 2006, ECAI.

Web Spam Detection by Probability Mapping GraphSOMs and Graph Neural Networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2010, ICANN.

Advances in Neural Information Processing Paradigms

Lakhmi C. Jain, Franco Scarselli, Marco Maggini, 2009, Innovations in Neural Information Paradigms and Applications.

Recursive Networks: An Overview of Theoretical Results

Franco Scarselli, Marco Gori, Monica Bianchini, 1999 .

Graph Neural Networks for the Prediction of Protein-Protein Interfaces

Franco Scarselli, Monica Bianchini, Alberto Rossi, 2020, ESANN.

Molecular graph generation with Graph Neural Networks

M. Bianchini, F. Scarselli, P. Bongini, 2020, arXiv.org.

Solving graph data issues using a layered architecture approach with applications to web spam detection

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2013, Neural Networks.

Smart Gravimetric System for Enhanced Security of Accesses to Public Places Embedding a MobileNet Neural Network Classifier

Barbara Toniella Corradini, M. Bianchini, F. Scarselli, 2022, IEEE Transactions on Instrumentation and Measurement.

Understanding Human Sleep Behaviour by Machine Learning

Paolo Barsocchi, Franco Scarselli, Filippo Palumbo, 2018, Cognitive Infocommunications, Theory and Applications.

The Vapnik-Chervonenkis dimension of graph and recursive neural networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2018, Neural Networks.

A multi-stage GAN for multi-organ chest X-ray image generation and segmentation pdf

Franco Scarselli, Monica Bianchini, Paolo Andreini, 2021, Mathematics.

Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities

Miquel Ferriol Galmés, F. Scarselli, A. Cabellos-Aparicio, 2021, IEEE Network.

Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results

Ah Chung Tsoi, Franco Scarselli, A. Tsoi, 1998, Neural Networks.

Face Spotting in Color Images using Recursive Neural Networks

Franco Scarselli, Monica Bianchini, Lorenzo Sarti, 2003 .

An unobtrusive sleep monitoring system for the human sleep behaviour understanding

Paolo Barsocchi, Franco Scarselli, Filippo Palumbo, 2016, 2016 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom).

A Comparative Study of Inductive and Transductive Learning with Feedforward Neural Networks

Franco Scarselli, Monica Bianchini, Anas Belahcen, 2016, AI*IA.

Recursive neural networks for processing graphs with labelled edges: theory and applications

Franco Scarselli, Marco Maggini, Monica Bianchini, 2005, Neural Networks.

Processing directed acyclic graphs with recursive neural networks

Franco Scarselli, Marco Gori, Monica Bianchini, 2001, IEEE Trans. Neural Networks.

Image generation by GAN and style transfer for agar plate image segmentation

Franco Scarselli, Alessandro Mecocci, Monica Bianchini, 2019, Comput. Methods Programs Biomed..

A Study on the effects of recursive convolutional layers in convolutional neural networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2021, Neurocomputing.

Graphical-Based Learning Environments for Pattern Recognition

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2004, SSPR/SPR.

Computational capabilities of linear recursive networks

Franco Scarselli, Marco Gori, Monica Bianchini, 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities

M. Bianchini, F. Scarselli, Andrea Passerini, 2023, ArXiv.

Sentence Extraction by Graph Neural Networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2010, ICANN.

Inside PageRank

Franco Scarselli, Marco Gori, Monica Bianchini, 2005, TOIT.

Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities

M. Bianchini, F. Scarselli, Andrea Passerini, 2023, ArXiv.

On the approximation capability of GNNs in node classification/regression tasks

M. Bianchini, F. Scarselli, M. Sampoli, 2021, 2106.08992.

A Deep Learning Approach to Analyze NMR Spectra of SH-SY5Y Cells for Alzheimer’s Disease Diagnosis

M. Bianchini, F. Scarselli, D. Valensin, 2023, Mathematics.

Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs

F. Scarselli, J. M. Thomas, C. Graziani, 2022, ArXiv.

Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation

Franco Scarselli, Monica Bianchini, Paolo Andreini, 2019, Pattern Recognit. Lett..

A Neural Network Approach to Web Graph Processing

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2005, APWeb.

Modular Multi–Source Prediction of Drug Side–Effects With DruGNN

Giovanna Maria Dimitri, M. Bianchini, F. Scarselli, 2022, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A Deep Learning Approach to Bacterial Colony Segmentation

Franco Scarselli, Alessandro Mecocci, Monica Bianchini, 2018, ICANN.

Going Deeper with Recursive Convolutional Layers

F. Scarselli, M. Hagenbuchner, Johan Chagnon, 2023, IEEE International Joint Conference on Neural Network.

Molecular generative Graph Neural Networks for Drug Discovery

M. Bianchini, F. Scarselli, P. Bongini, 2020, Neurocomputing.

GNNkeras: A Keras-based library for Graph Neural Networks and homogeneous and heterogeneous graph processing

M. Bianchini, F. Scarselli, P. Bongini, 2022, SoftwareX.

Segmentation of Aorta 3D CT Images Based on 2D Convolutional Neural Networks

Franco Scarselli, Alessandro Mecocci, Giovanna Maria Dimitri, 2021, Electronics.

Multi-Modal Siamese Network for Diagnostically Similar Lesion Retrieval in Prostate MRI

Franco Scarselli, Monica Bianchini, Alberto Rossi, 2020, IEEE Transactions on Medical Imaging.

On the Extension of the Weisfeiler-Lehman Hierarchy by WL Tests for Arbitrary Graphs

F. Scarselli, C. Graziani, Alice Moallemy-Oureh, 2022 .

Computing customized page ranks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2006, TOIT.

SortNet: Learning to Rank by a Neural Preference Function

Franco Scarselli, Marco Maggini, Leonardo Rigutini, 2011, IEEE Transactions on Neural Networks.

Inductive-Transductive Learning with Graph Neural Networks

Franco Scarselli, Giovanna Maria Dimitri, Marco Maggini, 2018, ANNPR.

Recursive processing of cyclic graphs

Franco Scarselli, Marco Gori, Monica Bianchini, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Recursive processing of cyclic graphs

Franco Scarselli, Marco Gori, Monica Bianchini, 2006, IEEE Transactions on Neural Networks.

Confidence Measures for Deep Learning in Domain Adaptation

Franco Scarselli, Akshay Pai, Monica Bianchini, 2019, Applied Sciences.

On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures

M. Bianchini, F. Scarselli, 2014, IEEE Transactions on Neural Networks and Learning Systems.

On the closure of the set of functions that can be realized by a given multilayer perceptron

Ah Chung Tsoi, Franco Scarselli, Marco Gori, 1998, IEEE Trans. Neural Networks.

Which classes of functions can a given multilayer perceptron approximate?

Ah Chung Tsoi, Marco Gori, F. Scarselli, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Recursive neural networks learn to localize faces

Franco Scarselli, Marco Maggini, Monica Bianchini, 2005, Pattern Recognit. Lett..

On the approximation capability of GNNs in node classification/regression tasks

M. Bianchini, F. Scarselli, M. Sampoli, 2021, 2106.08992.

Deep Neural Networks for Structured Data

Franco Scarselli, Giovanna Maria Dimitri, Marco Maggini, 2018 .

Graph Neural Networks for the Prediction of Protein-Protein Interfaces

M. Bianchini, F. Scarselli, S. Bonechi, 2020, ESANN.

A topological description of loss surfaces based on Betti Numbers

Maria Sofia Bucarelli, M. Bianchini, F. Scarselli, 2024, ArXiv.

Learning long-term dependencies using layered graph neural networks

Franco Scarselli, Monica Bianchini, Niccoló Bandinelli, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

2005 Special Issue: Recursive neural networks for processing graphs with labelled edges: theory and applications

M. Bianchini, F. Scarselli, Marco Maggini, 2005 .

Recursive neural networks for object detection

M. Maggini, F. Scarselli, L. Sarti, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

BackPropagation through Cyclic Structures

Franco Scarselli, Marco Gori, Monica Bianchini, 2003, AI*IA.

Face Localization with Recursive Neural Networks

Franco Scarselli, Marco Gori, Monica Bianchini, 2003, WIRN.

Processing directed acyclic graphs with recursive neural networks

M. Bianchini, F. Scarselli, M. Gori, 2001, IEEE Trans. Neural Networks.

A Hybrid Model for the Prediction of the Linguistic Origin of Surnames

Franco Scarselli, Marco Gori, Marco Maggini, 2003, IEEE Trans. Knowl. Data Eng..

A connectionist-based model for predicting the linguistic origin of surnames

Franco Scarselli, Marco Gori, Patrizia Bonaventura, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Adaptive page ranking with neural networks

Ah Chung Tsoi, Franco Scarselli, Markus Hagenbuchner, 2005, WWW '05.

Design of a crawler with bounded bandwidth

Franco Scarselli, Marco Maggini, Michelangelo Diligenti, 2004, WWW Alt. '04.