79 citations · 424 across the 54 of their papers we have counts for
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Conformal Quantitative Predictive Monitoring of STL Requirements for Stochastic Processes
Francesca Cairoli, Nicola Paoletti, Luca Bortolussi
We consider the problem of predictive monitoring (PM), i.e., predicting at runtime the satisfaction of a desired property from the current system's state. Due to its relevance for…
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
Luca Bortolussi, Ginevra Carbone, Luca Laurenti +3
Vulnerability to adversarial attacks is one of the principal hurdles to the adoption of deep learning in safety-critical applications. Despite significant efforts, both practical a…
Graph Neural Networks for Propositional Model Counting
Gaia Saveri, Luca Bortolussi
Graph Neural Networks (GNNs) have been recently leveraged to solve several logical reasoning tasks. Nevertheless, counting problems such as propositional model counting (#SAT) are…
Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking
Luca Bortolussi, Francesca Cairoli, Ginevra Carbone +1
Parametric verification of linear temporal properties for stochastic models can be expressed as computing the satisfaction probability of a certain property as a function of the pa…
Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processes
Luca Bortolussi, Giuseppe Maria Gallo, Jan Křetínský +1
We introduce a similarity function on formulae of signal temporal logic (STL). It comes in the form of a kernel function, well known in machine learning as a conceptually and compu…