A. Jeyasothy, Th. Laugel, M.‑J. Lesot, Ch. Marsala, M. Detyniecki : “Integrating Prior Knowledge in Post-hoc Explanations”, Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'2022), vol. 1602, Communications in Computer and Information Science, Milan, Italy, pp. 707–719, (Springer) (2022)
V. Ballet, †. Xavier, J. Aigrain, Th. Laugel, P. Frossard, M. Detyniecki : “Imperceptible Adversarial Attacks on Tabular Data”, NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness and Privacy (Robust AI in FS 2019), Vancouver, Canada (2019)
Th. Laugel, M.‑J. Lesot, Ch. Marsala, X. Renard, M. Detyniecki : “Unjustified Classification Regions and Counterfactual Explanations In Machine Learning”, Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019. Lecture Notes in Computer Science, vol 11907, vol. 11907 (II), Lecture Notes in Computer Science, Würzburg, Germany, pp. 37-54 (2019)
Th. Laugel, M.‑J. Lesot, Ch. Marsala, X. Renard, M. Detyniecki : “The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations”, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI-19}, Macao, Macao, pp. 2801-2807, (International Joint Conferences on Artificial Intelligence Organization) (2019)
X. Renard, Th. Laugel, M.‑J. Lesot, Ch. Marsala, M. Detyniecki : “Detecting Potential Local Adversarial Examples for Human-Interpretable Defense”, Workshop on Recent Advances in Adversarial Learning (Nemesis) of the European Conference on Machine Learning and Principles of Practice of Knowledge Discovery in Databases (ECML-PKDD), Dublin, Ireland (2018)
Th. Laugel, X. Renard, M.‑J. Lesot, Ch. Marsala, M. Detyniecki : “Defining Locality for Surrogates in Post-hoc Interpretablity”, Workshop on Human Interpretability for Machine Learning (WHI) - International Conference on Machine Learning (ICML), Stockholm, Sweden (2018)
Th. Laugel, M.‑J. Lesot, Ch. Marsala, X. Renard, M. Detyniecki : “Comparison-based Inverse Classification for Interpretability in Machine Learning”, 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, Cadix, Spain, pp. 100-111, (Springer Verlag) (2018)