3 citations · 5 across the 4 of their papers we have counts for
4 papers
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations
Luca Marzari, Francesco Leofante, Ferdinando Cicalese +1
We study the problem of assessing the robustness of counterfactual explanations for deep learning models. We focus on altering model parameters an…
Robust Counterfactual Explanations in Machine Learning: A Survey
Junqi Jiang, Francesco Leofante, Antonio Rago +1
Counterfactual explanations (CEs) are advocated as being ideally suited to providing algorithmic recourse for subjects affected by the predictions of machine learning models. While…
Recourse under Model Multiplicity via Argumentative Ensembling (Technical Report)
Junqi Jiang, Antonio Rago, Francesco Leofante +1
Model Multiplicity (MM) arises when multiple, equally performing machine learning models can be trained to solve the same prediction task. Recent studies show that models obtained…
Robot Swarms as Hybrid Systems: Modelling and Verification
Stefan Schupp, Francesco Leofante, Leander Behr +2
A swarm robotic system consists of a team of robots performing cooperative tasks without any centralized coordination. In principle, swarms enable flexible and scalable solutions;…