Pseudo-Rehearsal for Continual Learning with Normalizing Flows. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (CoRR, 2020)

Efficient continual learning in neural networks with embedding regularization. - Jary Pomponi; Simone Scardapane; Vincenzo Lomonaco; Aurelio Uncini (Neurocomputing, 2020)

DeepRICH: learning deeply Cherenkov detectors. - Cristiano Fanelli; Jary Pomponi (Mach. Learn. Sci. Technol., 2020)

Avalanche: An End-to-End Library for Continual Learning. - Vincenzo Lomonaco; Lorenzo Pellegrini; Andrea Cossu; Antonio Carta; Gabriele Graffieti; Tyler L. Hayes; Matthias De Lange; Marc Masana; Jary Pomponi; Gido M. van de Ven; Martin Mundt; Qi She; et al. (CVPR Workshops, 2021)

Avalanche: an End-to-End Library for Continual Learning. - Vincenzo Lomonaco; Lorenzo Pellegrini; Andrea Cossu; Antonio Carta; Gabriele Graffieti; Tyler L. Hayes; Matthias De Lange; Marc Masana; Jary Pomponi; Gido M. van de Ven; Martin Mundt; Qi She; et al. (CoRR, 2021)

Bayesian Neural Networks with Maximum Mean Discrepancy regularization. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (Neurocomputing, 2021)

Structured Ensembles: An approach to reduce the memory footprint of ensemble methods. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (Neural Networks, 2021)

Pixle: a fast and effective black-box attack based on rearranging pixels. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (IJCNN, 2022)

A Probabilistic Re-Intepretation of Confidence Scores in Multi-Exit Models. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (Entropy, 2022)

Centroids Matching: an efficient Continual Learning approach operating in the embedding space. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (Trans. Mach. Learn. Res., 2022)

Rearranging Pixels is a Powerful Black-Box Attack for RGB and Infrared Deep Learning Models. - Jary Pomponi; Daniele Dántoni; Alessandro Nicolosi; Simone Scardapane (IEEE Access, 2023)

Continual learning with invertible generative models. - Jary Pomponi; Simone Scardapane; Aurelio Uncini (Neural Networks, 2023)

Goal-Oriented Communications Based on Recursive Early Exit Neural Networks. - Jary Pomponi; Mattia Merluzzi; Alessio Devoto; Mateus Pontes Mota; Paolo Di Lorenzo; Simone Scardapane (IEEECONF, 2024)

Adaptive Semantic Token Selection for AI-native Goal-oriented Communications. - Alessio Devoto; Jary Pomponi; Simone Petruzzi; Paolo Di Lorenzo; Simone Scardapane (GLOBECOM (Workshops), 2024)

NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks. - Matteo Gambella; Jary Pomponi; Simone Scardapane; Manuel Roveri (CoRR, 2024)

Cascaded Scaling Classifier: class incremental learning with probability scaling. - Jary Pomponi; Alessio Devoto; Simone Scardapane (CoRR, 2024)

Joint or Disjoint: Mixing Training Regimes for Early-Exit Models. - Bartlomiej Krzepkowski; Monika Michaluk; Franciszek Szarwacki; Piotr Kubaty; Jary Pomponi; Tomasz Trzcinski; Bartosz Wójcik; Kamil Adamczewski (CoRR, 2024)

Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning. - Alessio Devoto; Federico Alvetreti; Jary Pomponi; Paolo Di Lorenzo; Pasquale Minervini; Simone Scardapane (CoRR, 2024)

Conditional computation in neural networks: Principles and research trends. - Simone Scardapane; Alessandro Baiocchi; Alessio Devoto; Valerio Marsocci; Pasquale Minervini; Jary Pomponi (Intelligenza Artificiale, 2024)

Adaptive layer and token selection for efficient fine-tuning of vision transformers. - Alessio Devoto; Federico Alvetreti; Jary Pomponi; Paolo Di Lorenzo; Pasquale Minervini; Simone Scardapane (Neurocomputing, 2025)

Class Incremental Learning with probability dampening and cascaded gated classifier. - Jary Pomponi; Alessio Devoto; Simone Scardapane (Neurocomputing, 2025)

Adaptive Semantic Token Communication for Transformer-based Edge Inference. - Alessio Devoto; Jary Pomponi; Mattia Merluzzi; Paolo Di Lorenzo; Simone Scardapane (CoRR, 2025)