Metric Learning for Temporal Sequence Alignment. - Rémi Lajugie; Damien Garreau; Francis R. Bach; Sylvain Arlot (NIPS, 2014)

Comparison-Based Random Forests. - Siavash Haghiri; Damien Garreau; Ulrike von Luxburg (ICML, 2018)

When do random forests fail? - Cheng Tang; Damien Garreau; Ulrike von Luxburg (NeurIPS, 2018)

Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system. - Felix Schoeller; Mickaël Eskinazi; Damien Garreau (Cogn. Syst. Res., 2018)

Explaining the Explainer: A First Theoretical Analysis of LIME. - Damien Garreau; Ulrike von Luxburg (AISTATS, 2020)

Looking deeper into LIME. - Damien Garreau; Ulrike von Luxburg (CoRR, 2020)

NEWMA: A New Method for Scalable Model-Free Online Change-Point Detection. - Nicolas Keriven; Damien Garreau; Iacopo Poli (IEEE Trans. Signal Process., 2020)

An Analysis of LIME for Text Data. - Dina Mardaoui; Damien Garreau (AISTATS, 2021)

What does LIME really see in images? - Damien Garreau; Dina Mardaoui (ICML, 2021)

Comparison-based centrality measures. - Luca Rendsburg; Damien Garreau (Int. J. Data Sci. Anal., 2021)

How to scale hyperparameters for quickshift image segmentation. - Damien Garreau (AISTATS, 2022)

Comparing Feature Importance and Rule Extraction for Interpretability on Text Data. - Gianluigi Lopardo; Damien Garreau (ICPR Workshops (3), 2022)

SMACE: A New Method for the Interpretability of Composite Decision Systems. - Gianluigi Lopardo; Damien Garreau; Frédéric Precioso; Greger Ottosson (ECML/PKDD (1), 2022)

Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional Network. - Buntheng Ly; Sonny Finsterbach; Marta Nuñez Garcia; Pierre Jaïs; Damien Garreau; Hubert Cochet; Maxime Sermesant (STACOM@MICCAI, 2022)

A Sea of Words: An In-Depth Analysis of Anchors for Text Data. - Gianluigi Lopardo; Frédéric Precioso; Damien Garreau (AISTATS, 2023)

On the Robustness of Text Vectorizers. - Rémi Catellier; Samuel Vaiter; Damien Garreau (ICML, 2023)

Explainability as statistical inference. - Hugo Henri Joseph Senetaire; Damien Garreau; Jes Frellsen; Pierre-Alexandre Mattei (ICML, 2023)

Understanding Post-hoc Explainers: The Case of Anchors. - Gianluigi Lopardo; Frédéric Precioso; Damien Garreau (CoRR, 2023)

Faithful and Robust Local Interpretability for Textual Predictions. - Gianluigi Lopardo; Frédéric Precioso; Damien Garreau (CoRR, 2023)

Are ensembles getting better all the time? - Pierre-Alexandre Mattei; Damien Garreau (CoRR, 2023)

Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition. - Simon Bartels; Wouter Boomsma; Jes Frellsen; Damien Garreau (J. Mach. Learn. Res., 2023)

The Risks of Recourse in Binary Classification. - Hidde Fokkema; Damien Garreau; Tim van Erven (AISTATS, 2024)

GLEAMS: Bridging the Gap Between Local and Global Explanations. - Giorgio Visani; Vincenzo Stanzione; Damien Garreau (HI-AI@KDD, 2024)

Attention Meets Post-hoc Interpretability: A Mathematical Perspective. - Gianluigi Lopardo; Frédéric Precioso; Damien Garreau (ICML, 2024)

Workshop on Human-Interpretable AI. - Gabriele Ciravegna; Mateo Espinosa Zarlenga; Pietro Barbiero; Francesco Giannini; Zohreh Shams; Damien Garreau; Mateja Jamnik; Tania Cerquitelli (KDD, 2024)

CAM-Based Methods Can See Through Walls. - Magamed Taimeskhanov; Ronan Sicre; Damien Garreau (ECML/PKDD (7), 2024)

Feature Attribution from First Principles. - Magamed Taimeskhanov; Damien Garreau (CoRR, 2025)

MMD-Flagger: Leveraging Maximum Mean Discrepancy to Detect Hallucinations. - Kensuke Mitsuzawa; Damien Garreau (CoRR, 2025)