Improving an Ensemble of Neural Networks via a Novel Multi-class Decomposition Schema. - Antonio L. Alfeo; Mario G. C. A. Cimino; Guido Gagliardi (IJCCI, 2022)

Automatic Feature Extraction for Bearings' Degradation Assessment using Minimally Pre-processed Time series and Multi-modal Feature Learning. - Antonio L. Alfeo; Mario G. C. A. Cimino; Guido Gagliardi (IN4PL, 2022)

Fine-Grained Emotion Recognition Using Brain-Heart Interplay Measurements and eXplainable Convolutional Neural Networks. - Guido Gagliardi; Antonio Luca Alfeo; Vincenzo Catrambone; Mario G. C. A. Cimino; Maarten De Vos; Gaetano Valenza (NER, 2023)

Matching the Expert's Knowledge via a Counterfactual-Based Feature Importance Measure. - Antonio Luca Alfeo; Mario G. C. A. Cimino; Guido Gagliardi (PKDD/ECML Workshops (3), 2023)

Using Contrastive Learning to Inject Domain-Knowledge Into Neural Networks for Recognizing Emotions. - Guido Gagliardi; Antonio Luca Alfeo; Vincenzo Catrambone; Mario G. C. A. Cimino; Maarten De Vos; Gaetano Valenza (SSCI, 2023)

Improving Emotion Recognition Systems by Exploiting the Spatial Information of EEG Sensors. - Guido Gagliardi; Antonio Luca Alfeo; Vincenzo Catrambone; Diego Candia-Rivera; Mario G. C. A. Cimino; Gaetano Valenza (IEEE Access, 2023)

Recognizing Bearings' Degradation Stage Using Multimodal Autoencoder to Learn Features from Different Time Series. - Antonio Luca Alfeo; Mario G. C. A. Cimino; Guido Gagliardi (SN Comput. Sci., 2024)