Louenas Bounia

According to our database¹, Louenas Bounia authored at least 23 papers between 2021 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Bibliography

2025

Robust Explanations Through Uncertainty Decomposition: A Path to Trustworthier AI.

[BibT_eX]

[DOI]

CoRR, July, 2025

Enhancing the intelligibility of decision trees with concise and reliable probabilistic explanations.

[BibT_eX]

[DOI]

Louenas Bounia

Insaf Setitra

Data Knowl. Eng., 2025

Using Submodular Optimization to Approximate Minimum-Size Abductive Path Explanations for Tree-Based Models.

[BibT_eX]

[DOI]

Louenas Bounia

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Facial Empathy Analysis Through Deep Learning and Computer Vision Techniques in Mixed Reality Environments.

[BibT_eX]

[DOI]

Insaf Setitra

Domitile Lourdeaux

Louenas Bounia

Proceedings of the 17th International Conference on Agents and Artificial Intelligence, 2025

Computing Improved Explanations for Random Forests: k-Majoritary Reasons.

[BibT_eX]

[DOI]

Louenas Bounia

Insaf Setitra

Proceedings of the 17th International Conference on Agents and Artificial Intelligence, 2025

Computing an Approximating Version of a Minimum-Size Explanation for Boolean Decision Tree Classifiers.

[BibT_eX]

Louenas Bounia

Proceedings of the 17th International Conference on Agents and Artificial Intelligence, 2025

Calcul de meilleures explications pour les forêts aléatoires : Raisons k-majoritaires et Raisons probabilistes majoritaires.

[BibT_eX]

[DOI]

Louenas Bounia

Proceedings of the Extraction et Gestion des Connaissances, EGC 2025, 2025

Approximation des explications abductives de taille minimale : application aux arbres de décision binaires.

[BibT_eX]

[DOI]

Louenas Bounia

Proceedings of the Extraction et Gestion des Connaissances, EGC 2025, 2025

2024

Enhancing the Intelligibility of Boolean Decision Trees with Concise and Reliable Probabilistic Explanations.

[BibT_eX]

[DOI]

Louenas Bounia

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2024

Approximation des explications probabilistes via la minimisation super-modulaire.

[BibT_eX]

[DOI]

Louenas Bounia

Frédéric Koriche

Proceedings of the Extraction et Gestion des Connaissances, 2024

Améliorer l'intelligibilité des arbres de décision avec des explications probabilistes concises et fiables.

[BibT_eX]

[DOI]

Louenas Bounia

Proceedings of the Extraction et Gestion des Connaissances, 2024

2023

Modéles formels pour l'IA explicable: des explications pour les arbres de décision. (Formal Models for Explainable AI: Explanations for Decision Trees).

[BibT_eX]

[DOI]

Louenas Bounia

PhD thesis, 2023

Approximating probabilistic explanations via supermodular minimization.

[BibT_eX]

[DOI]

Louenas Bounia

Frédéric Koriche

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Impact of Weight Functions on Preferred Abductive Explanations for Decision Trees.

[BibT_eX]

[DOI]

Louenas Bounia

Matthieu Goliot

Anasse Chafik

Proceedings of the Workshops at the 31st International Conference on Case-Based Reasoning (ICCBR-WS 2023) co-located with the 31st International Conference on Case-Based Reasoning (ICCBR 2023), 2023

PyXAI : calculer en Python des explications pour des modèles d'apprentissage supervisé.

[BibT_eX]

[DOI]

Proceedings of the Extraction et Gestion des Connaissances, 2023

Sur les explications abductives préférées pour les arbres de décision et les forêts aléatoires.

[BibT_eX]