Damien Garreau

52 papers A* 8A 5Journal 32Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means. CoRR Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso, Damien Garreau, Pierre-Alexandre Mattei
2026	J	`jnl`	Towards Understanding Steering Strength. CoRR Magamed Taimeskhanov, Samuel Vaiter, Damien Garreau
2026	J	`jnl`	When Are Two Scores Better Than One? Investigating Ensembles of Diffusion Models. CoRR Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso, Damien Garreau, Pierre-Alexandre Mattei
2026	J	`jnl`	When Are Two Scores Better Than One? Investigating Ensembles of Diffusion Models. Trans. Mach. Learn. Res. Raphaël Razafindralambo, Rémy Sun, Damien Garreau, Frédéric Precioso, Pierre-Alexandre Mattei
2025	J	`jnl`	Are Ensembles Getting Better All the Time? J. Mach. Learn. Res. Pierre-Alexandre Mattei, Damien Garreau
2025	A*	`conf`	CAM-Based Methods Can See through Walls (Extended Abstract). IJCAI Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
2025	J	`jnl`	Feature Attribution from First Principles. CoRR Magamed Taimeskhanov, Damien Garreau
2025	J	`jnl`	MMD-Flagger: Leveraging Maximum Mean Discrepancy to Detect Hallucinations. CoRR Kensuke Mitsuzawa, Damien Garreau
2025	J	`jnl`	On The Variability of Concept Activation Vectors. CoRR Julia Wenkmann, Damien Garreau
2024	A*	`conf`	Attention Meets Post-hoc Interpretability: A Mathematical Perspective. ICML Gianluigi Lopardo, Frédéric Precioso, Damien Garreau
2024	J	`jnl`	Attention Meets Post-hoc Interpretability: A Mathematical Perspective. CoRR Gianluigi Lopardo, Frédéric Precioso, Damien Garreau
2024	—	`conf`	CAM-Based Methods Can See Through Walls. ECML/PKDD (7) Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
2024	J	`jnl`	CAM-Based Methods Can See through Walls. CoRR Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
2024	—	`conf`	GLEAMS: Bridging the Gap Between Local and Global Explanations. HI-AI@KDD Giorgio Visani, Vincenzo Stanzione, Damien Garreau
2024	J	`jnl`	GLEAMS: Bridging the Gap Between Local and Global Explanations. CoRR Giorgio Visani, Vincenzo Stanzione, Damien Garreau
2024	—	`ed.`	Proceedings of the KDD Workshop on Human-Interpretable AI 2024 co-located with 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), Centre de Convencions Internacional de Barcelona, Spain, August 26, 2024. HI-AI@KDD Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Francesco Giannini, Damien Garreau, Mateja Jamnik, Tania Cerquitelli
2024	A	`conf`	The Risks of Recourse in Binary Classification. AISTATS Hidde Fokkema, Damien Garreau, Tim van Erven
2024	A*	`conf`	Workshop on Human-Interpretable AI. KDD Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli
2023	A	`conf`	A Sea of Words: An In-Depth Analysis of Anchors for Text Data. AISTATS Gianluigi Lopardo, Frédéric Precioso, Damien Garreau
2023	J	`jnl`	Are ensembles getting better all the time? CoRR Pierre-Alexandre Mattei, Damien Garreau
2023	A*	`conf`	Explainability as statistical inference. ICML Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
2023	J	`jnl`	Faithful and Robust Local Interpretability for Textual Predictions. CoRR Gianluigi Lopardo, Frédéric Precioso, Damien Garreau
2023	J	`jnl`	Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition. J. Mach. Learn. Res. Simon Bartels, Wouter Boomsma, Jes Frellsen, Damien Garreau
2023	A*	`conf`	On the Robustness of Text Vectorizers. ICML Rémi Catellier, Samuel Vaiter, Damien Garreau
2023	J	`jnl`	On the Robustness of Text Vectorizers. CoRR Rémi Catellier, Samuel Vaiter, Damien Garreau
2023	J	`jnl`	The Risks of Recourse in Binary Classification. CoRR Hidde Fokkema, Damien Garreau, Tim van Erven
2023	J	`jnl`	Understanding Post-hoc Explainers: The Case of Anchors. CoRR Gianluigi Lopardo, Frédéric Precioso, Damien Garreau
2022	J	`jnl`	A Sea of Words: An In-Depth Analysis of Anchors for Text Data. CoRR Gianluigi Lopardo, Damien Garreau, Frédéric Precioso
2022	—	`conf`	Comparing Feature Importance and Rule Extraction for Interpretability on Text Data. ICPR Workshops (3) Gianluigi Lopardo, Damien Garreau
2022	J	`jnl`	Comparing Feature Importance and Rule Extraction for Interpretability on Text Data. CoRR Gianluigi Lopardo, Damien Garreau
2022	J	`jnl`	Explainability as statistical inference. CoRR Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
2022	A	`conf`	How to scale hyperparameters for quickshift image segmentation. AISTATS Damien Garreau
2022	J	`jnl`	How to scale hyperparameters for quickshift image segmentation. CoRR Damien Garreau
2022	—	`conf`	Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional Network. STACOM@MICCAI Buntheng Ly, Sonny Finsterbach, Marta Nuñez Garcia, Pierre Jaïs, Damien Garreau, Hubert Cochet, Maxime Sermesant
2022	—	`conf`	SMACE: A New Method for the Interpretability of Composite Decision Systems. ECML/PKDD (1) Gianluigi Lopardo, Damien Garreau, Frédéric Precioso, Greger Ottosson
2021	A	`conf`	An Analysis of LIME for Text Data. AISTATS Dina Mardaoui, Damien Garreau
2021	J	`jnl`	Comparison-based centrality measures. Int. J. Data Sci. Anal. Luca Rendsburg, Damien Garreau
2021	J	`jnl`	SMACE: A New Method for the Interpretability of Composite Decision Systems. CoRR Gianluigi Lopardo, Damien Garreau, Frédéric Precioso, Greger Ottosson
2021	A*	`conf`	What does LIME really see in images? ICML Damien Garreau, Dina Mardaoui
2021	J	`jnl`	What does LIME really see in images? CoRR Damien Garreau, Dina Mardaoui
2020	J	`jnl`	An Analysis of LIME for Text Data. CoRR Dina Mardaoui, Damien Garreau
2020	A	`conf`	Explaining the Explainer: A First Theoretical Analysis of LIME. AISTATS Damien Garreau, Ulrike von Luxburg
2020	J	`jnl`	Explaining the Explainer: A First Theoretical Analysis of LIME. CoRR Damien Garreau, Ulrike von Luxburg
2020	J	`jnl`	Looking deeper into LIME. CoRR Damien Garreau, Ulrike von Luxburg
2020	J	`jnl`	NEWMA: A New Method for Scalable Model-Free Online Change-Point Detection. IEEE Trans. Signal Process. Nicolas Keriven, Damien Garreau, Iacopo Poli
2018	A*	`conf`	Comparison-Based Random Forests. ICML Siavash Haghiri, Damien Garreau, Ulrike von Luxburg
2018	J	`jnl`	Comparison-Based Random Forests. CoRR Siavash Haghiri, Damien Garreau, Ulrike von Luxburg
2018	J	`jnl`	Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system. Cogn. Syst. Res. Felix Schoeller, Mickaël Eskinazi, Damien Garreau
2018	J	`jnl`	NEWMA: a new method for scalable model-free online change-point detection. CoRR Nicolas Keriven, Damien Garreau, Iacopo Poli
2018	A*	`conf`	When do random forests fail? NeurIPS Cheng Tang, Damien Garreau, Ulrike von Luxburg
2014	—	`conf`	Metric Learning for Temporal Sequence Alignment. NIPS Rémi Lajugie, Damien Garreau, Francis R. Bach, Sylvain Arlot
2014	J	`jnl`	Metric Learning for Temporal Sequence Alignment. CoRR Damien Garreau, Rémi Lajugie, Sylvain Arlot, Francis R. Bach