Guillaume Staerman
Publications and Preprints
Point Processes and Physiological signals (MEG, EEG, ECG)
Flexible Parametric Inference for Space-Time Hawkes Processes (Submitted)
Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau [arxiv]
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels (ICML 2023)
Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau [arxiv]
Robust Inference
A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions (TMLR, 2024)
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon, Florence d'Alché-Buc [arxiv, code]
Affine-Invariant Integrated Rank-Weighted Depth:
Definition, Properties and Finite Sample Analysis (Electronic Journal of Statistics, 2023)
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon [paper, code]
When OT meets MoM: Robust estimation of Wasserstein Distance (AISTATS 2021)
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc [arxiv, code]
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure (AISTATS 2020, oral)
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon [arxiv, code]
Anomaly Detection
Signature Isolation Forest (AISTATS 2025)
Guillaume Staerman, Marta Campi, Gareth W. Peters, Tomoko Matsui [arxiv]
Unsupervised Layer-wise Score Aggregation for Textual OOD Detection (AAAI 2024)
Maxime Darrin, Guillaume Staerman, Eduardo Gomes, Jackie CK Cheung, Pablo Piantanida, Pierre Colombo [arxiv]
A Functional Perspective on Multi-Layer Out-of-Distribution Detection (Submitted)
Eduardo Gomes, Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida [openreview]
Toward Stronger Textual Attack Detectors (EMNLP 2023)
Pierre Colombo, Guillaume Staerman, Marine Picot, Nathan Noiry, Pablo Piantanida [paper]
A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection (TMLR, 2023)
Marine Picot, Frederica Granese, Guillaume Staerman, Marco Romanelli, Francisco Messina, Pablo Piantanida, Pierre Colombo [openreview]
A Simple Unsupervised Data Depth-based Method to Detect Adversarial Images (Submitted)
Marine Picot, Guillaume Staerman, Nathan Noiry, Francisco Messina, Pablo Piantanida, Pierre Colombo [openreview]
Beyond Mahalanobis-based Scores for Textual OOD Detection (NeurIPS 2022)
Pierre Colombo, Eduardo Gomes, Guillaume Staerman, Nathan Noiry, Pablo Piantanida  
Functional Anomaly Detection: a Benchmark Study (JDSA 2022)
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stephan Clémençon [arxiv]
Functional Isolation Forest (ACML 2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon, Florence d'Alché-Buc [arxiv, code]
Applications to NLP
Enhanced Hallucination Detection in Neural Machine Translation through Simple Detector Aggregation (EMNLP 2024)
Anas Himmi, Guillaume Staerman, Marine Picot, Pierre Colombo, Nuno Miguel Guerreiro [arxiv]
A Novel Information Theoretic Objective to Disentangle Representations for Fair Textual Classification (AACL 2023) Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida [arxiv]
Learning Disentangled Textual Representations via Statistical Measures of Similarity (ACL 2022, oral)
Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida [arxiv]
Automatic Text Evaluation through the Lens of Wasserstein Barycenters (EMNLP 2021, oral)
Pierre Colombo, Guillaume Staerman, Chloé Clavel, Pablo Piantanida [arxiv, code]
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