On the Finite State Machine Associated to an Adaptable Boolean Neural Net. - Francesco E. Lauria; Roberto Prevete; Marta Milo; S. Visco (ICONIP (1), 1997)

A Boolean Neural Network as a Rule Based System Learning New Rules by Examples. - Francesco E. Lauria; Roberto Prevete; Marta Milo; S. Visco (ICONIP, 1998)

A Boolean Neural Network Controlling Task Sequences in a Noisy Environment. - Francesco E. Lauria; Marta Milo; Roberto Prevete; S. Visco (IWANN (1), 1999)

An Adaptable Boolean Neural Network Performing Specific Sequence Learning. - Francesco E. Lauria; Roberto Prevete; Marta Milo (IJCNN (3), 2000)

Open Domain Question/Answering on the Web. - Bernardo Magnini; Matteo Negri; Roberto Prevete (AI*IA, 2001)

Multilingual Question/Answering: the DIOGENE System. - Bernardo Magnini; Matteo Negri; Roberto Prevete; Hristo Tanev (TREC, 2001)

Specific Sequence Learning by an Adaptable Boolean Neural Network. - Francesco E. Lauria; Roberto Prevete (WIRN, 2001)

Is It the Right Answer? Exploiting Web Redundancy for Answer Validation. - Bernardo Magnini; Matteo Negri; Roberto Prevete; Hristo Tanev (ACL, 2002)

Towards Automatic Evaluation of Question/Answering Systems. - Bernardo Magnini; Matteo Negri; Roberto Prevete; Hristo Tanev (LREC, 2002)

Mining Knowledge from Repeated Co-Occurrences: DIOGENE at TREC 2002. - Bernardo Magnini; Matteo Negri; Roberto Prevete; Hristo Tanev (TREC, 2002)

Computer aided detection of clustered microcalcifications in digitized mammograms using Gabor functions. - Ezio Catanzariti; Monica Ciminello; Roberto Prevete (ICIAP, 2003)

MEDIARAD: A Multiplatform Software Environment for Developing Imaging Applications in RADiology. - Ezio Catanzariti; Roberto Prevete; Matteo Santoro (CAMP, 2005)

Mass Detection in Mammograms Using Gabor Filters and Fuzzy Clustering. - Matteo Santoro; Roberto Prevete; L. Cavallo; Ezio Catanzariti (WILF, 2005)

A Neural Network Model for a View Independent Extraction of Reach-to-Grasp Action Features. - Roberto Prevete; Matteo Santoro; Ezio Catanzariti; Giovanni Tessitore (BVAI, 2007)

CTRNN Parameter Learning using Differential Evolution. - Ivanoe De Falco; Antonio Della Cioppa; Francesco Donnarumma; Domenico Maisto; Roberto Prevete; Ernesto Tarantino (ECAI, 2008)

A Semi-automated Method for the Measurement of the Fetal Nuchal Translucency in Ultrasound Images. - Ezio Catanzariti; Giovanni Fusco 004; Francesco Isgrò; Salvatore Masecchia; Roberto Prevete; Matteo Santoro (ICIAP, 2009)

An Action-tuned Neural Network Architecture for Hand Pose Estimation. - Giovanni Tessitore; Francesco Donnarumma; Roberto Prevete (IJCCI (ICFC-ICNC), 2010)

From motor to sensory processing in mirror neuron computational modelling. - Giovanni Tessitore; Roberto Prevete; Ezio Catanzariti; Guglielmo Tamburrini (Biol. Cybern., 2010)

A Robotic Scenario for Programmable Fixed-Weight Neural Networks Exhibiting Multiple Behaviors. - Guglielmo Montone; Francesco Donnarumma; Roberto Prevete (ICANNGA (1), 2011)

Perceiving affordances: A computational investigation of grasping affordances. - Roberto Prevete; Giovanni Tessitore; Ezio Catanzariti; Guglielmo Tamburrini (Cogn. Syst. Res., 2011)

Designing Structured Sparse Dictionaries for Sparse Representation Modeling. - Giovanni Tessitore; Roberto Prevete (Computer Recognition Systems 4, 2011)

Programming in the brain: a neural network theoretical framework. - Francesco Donnarumma; Roberto Prevete; Giuseppe Trautteur (Connect. Sci., 2012)

A system for the automatic measurement of the nuchal translucency thickness from ultrasound video stream of the foetus. - Anna Anzalone; Giovanni Fusco 004; Francesco Isgrò; Emanuela Orlandi; Roberto Prevete; Giuseppa Sciortino; Domenico Tegolo; Cesare Valenti (CBMS, 2013)

A Programmer-Interpreter Neural Network Architecture for Prefrontal Cognitive Control. - Francesco Donnarumma; Roberto Prevete; Fabian Chersi; Giovanni Pezzulo (Int. J. Neural Syst., 2015)

A linear approach for sparse coding by a two-layer neural network. - Alessandro Montalto; Giovanni Tessitore; Roberto Prevete (Neurocomputing, 2015)

Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality. - Alessandro Montalto; Sebastiano Stramaglia; Luca Faes; Giovanni Tessitore; Roberto Prevete; Daniele Marinazzo (Neural Networks, 2015)

A machine learning approach for predictive maintenance for mobile phones service providers. - Anna Corazza; Francesco Isgrò; Luca Longobardo; Roberto Prevete (3PGCIC, 2016)

Learning programs is better than learning dynamics: A programmable neural network hierarchical architecture in a multi-task scenario. - Francesco Donnarumma; Roberto Prevete; Andrea de Giorgio; Guglielmo Montone; Giovanni Pezzulo (Adapt. Behav., 2016)

Ethics-aware Data Governance (Vision Paper). - Letizia Tanca; Paolo Atzeni; Davide Azzalini; Ilaria Bartolini; Luca Cabibbo; Luca Calderoni; Paolo Ciaccia; Valter Crescenzi; Juan Carlos De Martin; Selina Fenoglietto; Donatella Firmani; Sergio Greco; et al. (SEBD, 2018)

Sparse Dictionaries for the Explanation of Classification Systems. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini; Alessio Vietri (PIE@CAiSE, 2019)

Explaining classification systems using sparse dictionaries. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Andrea Sorrentino; Guglielmo Tamburrini (ESANN, 2019)

Contrastive Explanations to Classification Systems Using Sparse Dictionaries. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini (ICIAP (1), 2019)

Feasibility of cardiovascular risk assessment through non-invasive measurements. - Pasquale Arpaia; Renato Cuocolo; Francesco Donnarumma; Dario D'Andrea; Antonio Esposito 002; Nicola Moccaldi; Angela Natalizio; Roberto Prevete (MetroInd4.0&IoT, 2019)

A simple and efficient architecture for trainable activation functions. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Neurocomputing, 2019)

A General Approach to Compute the Relevance of Middle-Level Input Features. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (ICPR Workshops (3), 2020)

Preliminary validation of a measurement system for emotion recognition. - Andrea Apicella 001; Pasquale Arpaia; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (MeMeA, 2020)

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini (Int. J. Neural Syst., 2020)

A Wearable EEG Instrument for Real-Time Frontal Asymmetry Monitoring in Worker Stress Analysis. - Pasquale Arpaia; Nicola Moccaldi; Roberto Prevete; Isabella Sannino; Annarita Tedesco (IEEE Trans. Instrum. Meas., 2020)

Dynamic Filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (CoRR, 2021)

A general approach for Explanations in terms of Middle Level Features. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (CoRR, 2021)

Beam Measurements and Machine Learning at the CERN Large Hadron Collider. - Pasquale Arpaia; Gabriella Azzopardi; Frédéric Blanc; Xavier Buffat; Loic Coyle; Elena Fol; Francesco Giordano; Massimo Giovannozzi; Tatiana Pieloni; Roberto Prevete; Stefano Redaelli; Belen Salvachua; et al. (IEEE Instrum. Meas. Mag., 2021)

A survey on modern trainable activation functions. - Andrea Apicella 001; Francesco Donnarumma; Francesco Isgrò; Roberto Prevete (Neural Networks, 2021)

XAI Approach for Addressing the Dataset Shift Problem: BCI as a Case Study (short paper). - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (BEWARE@AI*IA, 2022)

Toward the Application of XAI Methods in EEG-based Systems. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (XAI.it@AI*IA, 2022)

Neural Network-Based Prediction and Monitoring of Blood Glucose Response to Nutritional Factors in Type-1 Diabetes. - Leopoldo Angrisani; Giovanni Annuzzi; Pasquale Arpaia; Lutgarda Bozzetto; Andrea Cataldo; Alessandra Corrado; Egidio De Benedetto; Vincenzo Di Capua; Roberto Prevete; Ersilia Vallefuoco (I2MTC, 2022)

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces. - Leopoldo Angrisani; Andrea Apicella 001; Pasquale Arpaia; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (I2MTC, 2022)

Adoption of Machine Learning Techniques to Enhance Classification Performance in Reactive Brain-Computer Interfaces. - Andrea Apicella 001; Pasquale Arpaia; Andrea Cataldo; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (MeMeA, 2022)

On The Effects Of Data Normalisation For Domain Adaptation On EEG Data. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (CoRR, 2022)

Machine Learning Strategies to Improve Generalization in EEG-based Emotion Assessment: a Systematic Review. - Andrea Apicella 001; Pasquale Arpaia; Giovanni D'Errico; Davide Marocco; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (CoRR, 2022)

Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (Knowl. Based Syst., 2022)

SHAP-based Explanations to Improve Classification Systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (XAI.it@AI*IA, 2023)

An XAI-Based Masking Approach to Improve Classification Systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (BEWARE@AI*IA, 2023)

Dynamic Local Filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (ICIAP (2), 2023)

Toward the Improvement of Probabilistic Classifiers Using Ontologies. - Andrea Apicella 001; Anna Corazza; Francesco Isgrò; Roberto Prevete (MetroXRAINE, 2023)

Strategies to Exploit XAI to Improve Classification Systems. - Andrea Apicella 001; Luca Di Lorenzo; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (xAI (1), 2023)

Impact of Nutritional Factors in Blood Glucose Prediction in Type 1 Diabetes Through Machine Learning. - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Sabatina Criscuolo; Egidio De Benedetto; Marisa Pesola; Roberto Prevete; Ersilia Vallefuoco (IEEE Access, 2023)

Employment of Domain Adaptation Techniques in SSVEP-Based Brain-Computer Interfaces. - Andrea Apicella 001; Pasquale Arpaia; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (IEEE Access, 2023)

Semi-Supervised Detection of Structural Damage Using Variational Autoencoder and a One-Class Support Vector Machine. - Andrea Pollastro; Giusiana Testa; Antonio Bilotta; Roberto Prevete (IEEE Access, 2023)

Hidden Classification Layers: a study on Data Hidden Representations with a Higher Degree of Linear Separability between the Classes. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (CoRR, 2023)

On the effects of data normalization for domain adaptation on EEG data. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (Eng. Appl. Artif. Intell., 2023)

Adaptive filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (Pattern Recognit., 2023)

Improving the Performance of Already Trained Classifiers Through an Automatic Explanation-Based Learning Approach. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (DS (2), 2024)

Advancing Healthcare Through AI: Innovations in Monitoring and Diagnostic Technologies at the Augmented Reality for Health Monitoring Laboratory (ARHeMLab). - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Umberto Bracale; Egidio De Benedetto; Paolo De Blasiis; Antonio Esposito 002; Francesco Isgrò; Giacomo Lus; Nicola Moccaldi; Roberto Peltrini; et al. (Ital-IA, 2024)

A Comparative Analysis Between Quantum Machine Learning and Machine Learning on EEG Dataset. - Leopoldo Angrisani; Egidio De Benedetto; Alessandro Di Bernardo; Roberto Prevete; Annarita Tedesco (MetroXRAINE, 2024)

Towards a general framework for improving the performance of classifiers using XAI methods. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (CoRR, 2024)

SincVAE: a New Approach to Improve Anomaly Detection on EEG Data Using SincNet and Variational Autoencoder. - Andrea Pollastro; Francesco Isgrò; Roberto Prevete (CoRR, 2024)

Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods. - Andrea Apicella 001; Pasquale Arpaia; Giovanni D'Errico; Davide Marocco; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (Neurocomputing, 2024)

Hidden classification layers: Enhancing linear separability between classes in neural networks layers. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Pattern Recognit. Lett., 2024)

Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI. - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Sabatina Criscuolo; Egidio De Benedetto; Marisa Pesola; Roberto Prevete (IEEE J. Biomed. Health Informatics, 2024)

Enhancing EEG-Based MI-BCIs with Class-Specific and Subject-Specific Features Detected by Neural Manifold Analysis. - Mirco Frosolone; Roberto Prevete; Lorenzo Ognibeni; Salvatore Giugliano; Andrea Apicella 001; Giovanni Pezzulo; Francesco Donnarumma (Sensors, 2024)

Interpreting the latent space of a Convolutional Variational Autoencoder for semi-automated eye blink artefact detection in EEG signals. - Sabatina Criscuolo; Andrea Apicella 001; Roberto Prevete; Luca Longo (Comput. Stand. Interfaces, 2025)

IMPACTX: Improving Model Performance by Appropriately predicting CorrecT eXplanations. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (CoRR, 2025)

Don't push the button! Exploring data leakage risks in machine learning and transfer learning. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Artif. Intell. Rev., 2025)