Functional Isolation Forest. - Guillaume Staerman; Pavlo Mozharovskyi; Stéphan Clémençon; Florence d'Alché-Buc (ACML, 2019)

The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure. - Guillaume Staerman; Pavlo Mozharovskyi; Stéphan Clémençon (AISTATS, 2020)

How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers. - Pierre Laforgue; Guillaume Staerman; Stéphan Clémençon (CoRR, 2020)

When OT meets MoM: Robust estimation of Wasserstein Distance. - Guillaume Staerman; Pierre Laforgue; Pavlo Mozharovskyi; Florence d'Alché-Buc (AISTATS, 2021)

Automatic Text Evaluation through the Lens of Wasserstein Barycenters. - Pierre Colombo; Guillaume Staerman; Chloé Clavel; Pablo Piantanida (EMNLP (1), 2021)

Generalization Bounds in the Presence of Outliers: a Median-of-Means Study. - Pierre Laforgue; Guillaume Staerman; Stéphan Clémençon (ICML, 2021)

Depth-based pseudo-metrics between probability distributions. - Guillaume Staerman; Pavlo Mozharovskyi; Stéphan Clémençon; Florence d'Alché-Buc (CoRR, 2021)

Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis. - Guillaume Staerman; Pavlo Mozharovskyi; Stéphan Clémençon (CoRR, 2021)

Learning Disentangled Textual Representations via Statistical Measures of Similarity. - Pierre Colombo; Guillaume Staerman; Nathan Noiry; Pablo Piantanida (ACL (1), 2022)

Beyond Mahalanobis Distance for Textual OOD Detection. - Pierre Colombo; Eduardo Dadalto Câmara Gomes; Guillaume Staerman; Nathan Noiry; Pablo Piantanida (NeurIPS, 2022)

Beyond Mahalanobis-Based Scores for Textual OOD Detection. - Pierre Colombo; Eduardo Dadalto Câmara Gomes; Guillaume Staerman; Nathan Noiry; Pablo Piantanida (CoRR, 2022)

Toward Stronger Textual Attack Detectors. - Pierre Colombo; Marine Picot; Nathan Noiry; Guillaume Staerman; Pablo Piantanida (EMNLP (Findings), 2023)

Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability. - Anass Aghbalou; Guillaume Staerman (ICML, 2023)

FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels. - Guillaume Staerman; Cédric Allain; Alexandre Gramfort; Thomas Moreau 001 (ICML, 2023)

A Novel Information Theoretic Objective to Disentangle Representations for Fair Classification. - Pierre Colombo; Nathan Noiry; Guillaume Staerman; Pablo Piantanida (IJCNLP (Findings), 2023)

Hypothesis Transfer Learning with Surrogate Classification Losses. - Anass Aghbalou; Guillaume Staerman (CoRR, 2023)

A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection. - Eduardo Dadalto Câmara Gomes; Pierre Colombo; Guillaume Staerman; Nathan Noiry; Pablo Piantanida (CoRR, 2023)

A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection. - Marine Picot; Federica Granese; Guillaume Staerman; Marco Romanelli 002; Francisco Messina; Pablo Piantanida; Pierre Colombo (Trans. Mach. Learn. Res., 2023)

Functional anomaly detection: a benchmark study. - Guillaume Staerman; Eric Adjakossa; Pavlo Mozharovskyi; Vera Hofer; Jayant Sen Gupta; Stéphan Clémençon (Int. J. Data Sci. Anal., 2023)

Unsupervised Layer-Wise Score Aggregation for Textual OOD Detection. - Maxime Darrin; Guillaume Staerman; Eduardo Dadalto Câmara Gomes; Jackie C. K. Cheung; Pablo Piantanida; Pierre Colombo (AAAI, 2024)

Enhanced Hallucination Detection in Neural Machine Translation through Simple Detector Aggregation. - Anas Himmi; Guillaume Staerman; Marine Picot; Pierre Colombo; Nuno Miguel Guerreiro (EMNLP, 2024)

Signature Isolation Forest. - Guillaume Staerman; Marta Campi; Gareth W. Peters (CoRR, 2024)

Flexible Parametric Inference for Space-Time Hawkes Processes. - Emilia Siviero; Guillaume Staerman; Stéphan Clémençon; Thomas Moreau 001 (CoRR, 2024)

Unmixing Noise from Hawkes Process to Model Learned Physiological Events. - Guillaume Staerman; Virginie Loison; Thomas Moreau 001 (CoRR, 2024)

A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions. - Guillaume Staerman; Pavlo Mozharovskyi; Pierre Colombo; Stéphan Clémençon; Florence d'Alché-Buc (Trans. Mach. Learn. Res., 2024)

Signature Isolation Forest. - Marta Campi; Guillaume Staerman; Gareth W. Peters; Tomoko Masui (AISTATS, 2025)

UNHaP: Unmixing Noise from Hawkes Processes. - Virginie Loison; Guillaume Staerman; Thomas Moreau 001 (AISTATS, 2025)