5 papers
FedCMAPSS: A Benchmark for Federated Learning in Remaining Useful Life Estimation
Amelia Sorrenti, Matteo Pennisi, Concetto Spampinato +1
Data-driven prognostics and health management has emerged as a key enabler for Industry 4.0, yet the development of robust remaining useful life (RUL) estimation models is often li…
Dream2Learn: Structured Generative Dreaming for Continual Learning
Salvatore Calcagno, Matteo Pennisi, Federica Proietto Salanitri +4
Continual learning requires balancing plasticity and stability while mitigating catastrophic forgetting. Inspired by human dreaming as a mechanism for internal simulation and knowl…
DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models
Simone Carnemolla, Matteo Pennisi, Sarinda Samarasinghe +5
Understanding and explaining the behavior of machine learning models is essential for building transparent and trustworthy AI systems. We introduce DEXTER, a data-free framework th…
QuantFormer: Learning to Quantize for Neural Activity Forecasting in Mouse Visual Cortex
Salvatore Calcagno, Isaak Kavasidis, Simone Palazzo +8
Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecast neural activity crucial for developi…
Back to Supervision: Boosting Word Boundary Detection through Frame Classification
Simone Carnemolla, Salvatore Calcagno, Simone Palazzo +1
Speech segmentation at both word and phoneme levels is crucial for various speech processing tasks. It significantly aids in extracting meaningful units from an utterance, thus ena…