Personalization of monitoring system parameters to support ambulatory care for dementia patients. - Markus Schinle; Ioannis Papantonis; Wilhelm Stork (SAS, 2018)

Interventions and Counterfactuals in Tractable Probabilistic Models: Limitations of Contemporary Transformations. - Ioannis Papantonis; Vaishak Belle (CoRR, 2020)

On Constraint Definability in Tractable Probabilistic Models. - Ioannis Papantonis; Vaishak Belle (CoRR, 2020)

Principles and Practice of Explainable Machine Learning. - Vaishak Belle; Ioannis Papantonis (Frontiers Big Data, 2021)

Closed-Form Results for Prior Constraints in Sum-Product Networks. - Ioannis Papantonis; Vaishak Belle (Frontiers Artif. Intell., 2021)

Explainability in Machine Learning: a Pedagogical Perspective. - Andreas C. Bueff; Ioannis Papantonis; Auste Simkute; Vaishak Belle (CoRR, 2022)

Transparency in Sum-Product Network Decompilation. - Ioannis Papantonis; Vaishak Belle (ECAI, 2023)

Model Transparency: Why Do We Care? - Ioannis Papantonis; Vaishak Belle (ICAART (3), 2023)

Why not both? Complementing explanations with uncertainty, and the role of self-confidence in Human-AI collaboration. - Ioannis Papantonis; Vaishak Belle (CoRR, 2023)

Principled diverse counterfactuals in multilinear models. - Ioannis Papantonis; Vaishak Belle (Mach. Learn., 2024)