| Principles and practice of explainable machine learning V Belle, I Papantonis Frontiers in big Data 4, 688969, 2021 | 451 | 2021 |
| Closed-form results for prior constraints in sum-product networks I Papantonis, V Belle Frontiers in Artificial Intelligence 4, 644062, 2021 | 6 | 2021 |
| Principles and practice of explainable machine learning. arXiv 2020 V Belle, I Papantonis arXiv preprint arXiv:2009.11698, 2020 | 6 | 2020 |
| Principles and Practice of Explainable Machine Learning. Frontiers in Big Data 4 (2021) V Belle, I Papantonis URL https://www. frontiersin. org/articles/10.3389/fdata, 2021 | 5 | 2021 |
| Interventions and counterfactuals in tractable probabilistic models: Limitations of contemporary transformations I Papantonis, V Belle arXiv preprint arXiv:2001.10905, 2020 | 5 | 2020 |
| Principled diverse counterfactuals in multilinear models I Papantonis, V Belle Machine Learning, 1-23, 2024 | 3 | 2024 |
| Explainability in machine learning: a pedagogical perspective A Bueff, I Papantonis, A Simkute, V Belle arXiv preprint arXiv:2202.10335, 2022 | 2 | 2022 |
| Interventions and counterfactuals in tractable probabilistic models I Papantonis, V Belle NeurIPS workshop on knowledge representation & reasoning meets machine learning, 2019 | 2 | 2019 |
| Transparency: from tractability to model explanations I Papantonis The University of Edinburgh, 2023 | | 2023 |
| Why not both? Complementing explanations with uncertainty, and the role of self-confidence in Human-AI collaboration I Papantonis, V Belle arXiv preprint arXiv:2304.14130, 2023 | | 2023 |
| Model Transparency: Why Do We Care? I Papantonis, V Belle ICAART (3), 650-657, 2023 | | 2023 |
| Transparency in Sum-Product Network Decompilation I Papantonis, V Belle ECAI 2023, 1827-1834, 2023 | | 2023 |
Vaishak BelleUniversity of EdinburghVerified email at ed.ac.uk
