| 2025 | IJCAI | CAM-Based Methods Can See through Walls (Extended Abstract). | Magamed Taimeskhanov, Ronan Sicre, Damien Garreau |
| 2024 | AISTATS | The Risks of Recourse in Binary Classification. | Hidde Fokkema, Damien Garreau, Tim van Erven |
| 2024 | ICML | Attention Meets Post-hoc Interpretability: A Mathematical Perspective. | Gianluigi Lopardo, Frdric Precioso, Damien Garreau |
| 2024 | KDD | Workshop on Human-Interpretable AI. | Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli |
| 2023 | AISTATS | A Sea of Words: An In-Depth Analysis of Anchors for Text Data. | Gianluigi Lopardo, Frdric Precioso, Damien Garreau |
| 2023 | ICML | On the Robustness of Text Vectorizers. | Rmi Catellier, Samuel Vaiter, Damien Garreau |
| 2023 | ICML | Explainability as statistical inference. | Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei |
| 2022 | AISTATS | How to scale hyperparameters for quickshift image segmentation. | Damien Garreau |
| 2022 | ICPR | Comparing Feature Importance and Rule Extraction for Interpretability on Text Data. | Gianluigi Lopardo, Damien Garreau |
| 2021 | AISTATS | An Analysis of LIME for Text Data. | Dina Mardaoui, Damien Garreau |
| 2021 | ICML | What does LIME really see in images? | Damien Garreau, Dina Mardaoui |
| 2020 | AISTATS | Explaining the Explainer: A First Theoretical Analysis of LIME. | Damien Garreau, Ulrike von Luxburg |
| 2018 | ICML | Comparison-Based Random Forests. | Siavash Haghiri, Damien Garreau, Ulrike von Luxburg |