14 citations · 31 across the 6 of their papers we have counts for
6 papers
Towards the Formalization of a Trustworthy AI for Mining Interpretable Models explOiting Sophisticated Algorithms
Riccardo Guidotti, Martina Cinquini, Marta Marchiori Manerba +2
Interpretable-by-design models are crucial for fostering trust, accountability, and safe adoption of automated decision-making models in real-world applications. In this paper we f…
A Practical Approach to Causal Inference over Time
Martina Cinquini, Isacco Beretta, Salvatore Ruggieri +1
In this paper, we focus on estimating the causal effect of an intervention over time on a dynamical system. To that end, we formally define causal interventions and their effects o…
Constraint-Free Structure Learning with Smooth Acyclic Orientations
Riccardo Massidda, Francesco Landolfi, Martina Cinquini +1
The structure learning problem consists of fitting data generated by a Directed Acyclic Graph (DAG) to correctly reconstruct its arcs. In this context, differentiable approaches co…
The Importance of Time in Causal Algorithmic Recourse
Isacco Beretta, Martina Cinquini
The application of Algorithmic Recourse in decision-making is a promising field that offers practical solutions to reverse unfavorable decisions. However, the inability of these me…
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery
Martina Cinquini, Fosca Giannotti, Riccardo Guidotti
Synthetic data generation has been widely adopted in software testing, data privacy, imbalanced learning, and artificial intelligence explanation. In all such contexts, it is cruci…
Causality-Aware Local Interpretable Model-Agnostic Explanations
Martina Cinquini, Riccardo Guidotti
A main drawback of eXplainable Artificial Intelligence (XAI) approaches is the feature independence assumption, hindering the study of potential variable dependencies. This leads t…