Artificial Resilience in neuromorphic systems. - Alessio Carpegna; Stefano Di Carlo; Alessandro Savino (HEART, 2022)

Spiker: an FPGA-optimized Hardware accelerator for Spiking Neural Networks. - Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (ISVLSI, 2022)

Prediction of the Impact of Approximate Computing on Spiking Neural Networks via Interval Arithmetic. - Sepide Saeedi; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (LATS, 2022)

FPGA-optimized Hardware acceleration for Spiking Neural Networks. - Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2022)

Are micro-architectural features able to explain faulty executions in the presence of soft errors? A preliminary study. - Deniz Kasap; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2022)

Micro-Architectural features as soft-error markers in embedded safety-critical systems: preliminary study. - Deniz Kasap; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (ETS, 2023)

EUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS. - Fabio Pavanello; Cédric Marchand 002; Ian O'Connor; Régis Orobtchouk; Fabien Mandorlo; Xavier Letartre; Sébastien Cueff; Elena-Ioana Vatajelu; Giorgio Di Natale; Benoit Cluzel; Aurelien Coillet; Benoît Charbonnier; et al. (ETS, 2023)

Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies. - Fabio Pavanello; Elena-Ioana Vatajelu; Alberto Bosio; Thomas Van Vaerenbergh; Peter Bienstman; Benoît Charbonnier; Alessio Carpegna; Stefano Di Carlo; Alessandro Savino (VTS, 2023)

NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS. - Fabio Pavanello; Cédric Marchand 002; Ian O'Connor; Régis Orobtchouk; Fabien Mandorlo; Xavier Letartre; Sébastien Cueff; Elena-Ioana Vatajelu; Giorgio Di Natale; Benoit Cluzel; Aurelien Coillet; Benoît Charbonnier; et al. (CoRR, 2023)

Neuromorphic Heart Rate Monitors: Neural State Machines for Monotonic Change Detection. - Alessio Carpegna; Chiara De Luca; Federico Emanuele Pozzi; Alessandro Savino; Stefano Di Carlo; Giacomo Indiveri; Elisa Donati (BioCAS, 2024)

Fast Exploration of the Impact of Precision Reduction on Spiking Neural Networks. - Sepide Saeedi; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (DTTIS, 2024)

Approximate Fault-Tolerant Neural Network Systems. - Marcello Traiola; Salvatore Pappalardo; Ali Piri; Annachiara Ruospo; Bastien Deveautour; Ernesto Sánchez 001; Alberto Bosio; Sepide Saeedi; Alessio Carpegna; Anil Bayram Gogebakan; Enrico Magliano; Alessandro Savino (ETS, 2024)

SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks. - Anil Bayram Gögebakan; Enrico Magliano; Alessio Carpegna; Annachiara Ruospo; Alessandro Savino; Stefano Di Carlo (IOLTS, 2024)

Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks. - Alberto Dequino; Alessio Carpegna; Davide Nadalini; Alessandro Savino; Luca Benini; Stefano Di Carlo; Francesco Conti 001 (ISVLSI, 2024)

A Micro Architectural Events Aware Real-Time Embedded System Fault Injector. - Enrico Magliano; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (LATS, 2024)

Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge. - Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2024)

SpikeExplorer: hardware-oriented Design Space Exploration for Spiking Neural Networks on FPGA. - Dario Padovano; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2024)

Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons. - Filippo Marostica; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2025)

SFATTI: Spiking FPGA Accelerator for Temporal Task-driven Inference - A Case Study on MNIST. - Alessio Caviglia; Filippo Marostica; Alessio Carpegna; Alessandro Savino; Stefano Di Carlo (CoRR, 2025)