2 citations · 5 across the 4 of their papers we have counts for
4 papers
The CAISAR Platform: Extending the Reach of Machine Learning Specification and Verification
Michele Alberti, François Bobot, Julien Girard-Satabin +3
The formal specification and verification of machine learning programs saw remarkable progress in less than a decade, leading to a profusion of tools. However, diversity may lead t…
CAISAR: A platform for Characterizing Artificial Intelligence Safety and Robustness
Julien Girard-Satabin, Michele Alberti, François Bobot +2
We present CAISAR, an open-source platform under active development for the characterization of AI systems' robustness and safety. CAISAR provides a unified entry point for definin…
Context Generation from Formal Specifications for C Analysis Tools
Michele Alberti, Julien Signoles
Analysis tools like abstract interpreters, symbolic execution tools and testing tools usually require a proper context to give useful results when analyzing a particular function.…
On Coinductive Equivalences for Higher-Order Probabilistic Functional Programs (Long Version)
Ugo Dal Lago, Davide Sangiorgi, Michele Alberti
We study bisimulation and context equivalence in a probabilistic -calculus. The contributions of this paper are threefold. Firstly we show a technique for proving congruence of…