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Explaining the Explainers in Graph Neural Networks: a Comparative Study


Oct 27, 2022
Antonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Liò, Bruno Lepri, Andrea Passerini

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Global Explainability of GNNs via Logic Combination of Learned Concepts


Oct 14, 2022
Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Liò, Andrea Passerini

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Rethinking and Recomputing the Value of ML Models


Sep 30, 2022
Burcu Sayin, Fabio Casati, Andrea Passerini, Jie Yang, Xinyue Chen

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SMT-based Weighted Model Integration with Structure Awareness


Jun 28, 2022
Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani

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* Accepted for the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) 

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Concept-level Debugging of Part-Prototype Networks


May 31, 2022
Andrea Bontempelli, Stefano Teso, Fausto Giunchiglia, Andrea Passerini

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GlanceNets: Interpretabile, Leak-proof Concept-based Models


May 31, 2022
Emanuele Marconato, Andrea Passerini, Stefano Teso

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Generating personalized counterfactual interventions for algorithmic recourse by eliciting user preferences


May 27, 2022
Giovanni De Toni, Paolo Viappiani, Bruno Lepri, Andrea Passerini

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Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens


May 20, 2022
Stefano Teso, Laurens Bliek, Andrea Borghesi, Michele Lombardi, Neil Yorke-Smith, Tias Guns, Andrea Passerini

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Lifelong Personal Context Recognition


May 10, 2022
Andrea Bontempelli, Marcelo Rodas Britez, Xiaoyue Li, Haonan Zhao, Luca Erculiani, Stefano Teso, Andrea Passerini, Fausto Giunchiglia

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* 8 pages 

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Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis


Jan 18, 2022
Giovanni De Toni, Bruno Lepri, Andrea Passerini

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