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.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…
q-bio.QM2020
Computational Logic for Biomedicine and Neurosciences
Elisabetta de Maria, Joelle Despeyroux, Amy Felty +3
We advocate here the use of computational logic for systems biology, as a \emph{unified and safe} framework well suited for both modeling the dynamic behaviour of biological system…