3 papers
cs.NE2026
A Formal Tool for Verification of Probabilistic Spiking Neural Networks Based on Quotient Abstractions
Nikan Zandian Jazi, Elisabetta De Maria, Christopher Leturc
Spiking Neural Networks (SNNs) model biological neural dynamics more faithfully than classical artificial networks, but their stochastic, event-driven computation -- rooted in ion-…
cs.LO2026
Modelling and Verifying Neuronal Archetypes in Rocq
Abdorrahim Bahrami, Rébecca Zucchini, Elisabetta De Maria +1
Formal verification has become increasingly important because of the kinds of guarantees that it can provide for software systems. Verification of models of biological and medical…
cs.AI2025
Probabilistic Modeling of Spiking Neural Networks with Contract-Based Verification
Zhen Yao, Elisabetta De Maria, Robert De Simone
Spiking Neural Networks (SNN) are models for "realistic" neuronal computation, which makes them somehow different in scope from "ordinary" deep-learning models widely used in AI pl…