Robust Low-Rank Change Detection for Multivariate SAR Image Time Series. - Ammar Mian; Antoine Collas; Arnaud Breloy; Guillaume Ginolhac; Jean Philippe Ovarlez (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020)

A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization. - Antoine Collas; Florent Bouchard; Arnaud Breloy; Chenfang Ren; Guillaume Ginolhac; Jean Philippe Ovarlez (ICASSP, 2021)

Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering. - Antoine Collas; Florent Bouchard; Arnaud Breloy; Guillaume Ginolhac; Chengfang Ren; Jean Philippe Ovarlez (IEEE Trans. Signal Process., 2021)

Robust Geometric Metric Learning. - Antoine Collas; Arnaud Breloy; Guillaume Ginolhac; Chengfang Ren; Jean Philippe Ovarlez (EUSIPCO, 2022)

On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems. - Antoine Collas; Florent Bouchard; Guillaume Ginolhac; Arnaud Breloy; Chengfang Ren; Jean Philippe Ovarlez (ICASSP, 2022)

Géométrie riemannienne pour l'estimation et l'apprentissage statistiques : application à la télédétection. (Riemannian geometry for statistical estimation and learning : application to remote sensing). - Antoine Collas (2022)

Entropic Wasserstein Component Analysis. - Antoine Collas; Titouan Vayer; Rémi Flamary; Arnaud Breloy (MLSP, 2023)

The Fisher-Rao geometry of CES distributions. - Florent Bouchard; Arnaud Breloy; Antoine Collas; Alexandre Renaux; Guillaume Ginolhac (CoRR, 2023)

Riemannian Optimization for Non-Centered Mixture of Scaled Gaussian Distributions. - Antoine Collas; Arnaud Breloy; Chengfang Ren; Guillaume Ginolhac; Jean Philippe Ovarlez (IEEE Trans. Signal Process., 2023)

Parametric Information Geometry with the Package Geomstats. - Alice Le Brigant; Jules Deschamps; Antoine Collas; Nina Miolane (ACM Trans. Math. Softw., 2023)

Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. - Apolline Mellot; Antoine Collas; Sylvain Chevallier; Denis A. Engemann; Alexandre Gramfort (EUSIPCO, 2024)

Geodesic Optimization for Predictive Shift Adaptation on EEG data. - Apolline Mellot; Antoine Collas; Sylvain Chevallier; Alexandre Gramfort; Denis A. Engemann (NeurIPS, 2024)

Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. - Antoine Collas; Rémi Flamary; Alexandre Gramfort (CoRR, 2024)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Oleksii Kachaiev; Ambroise Odonnat; Alexandre Gramfort; Thomas Moreau 001; Rémi Flamary (CoRR, 2024)

Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Karim Lounici; Alexandre Gramfort (CoRR, 2024)

Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction. - Joseph Paillard; Antoine Collas; Denis A. Engemann; Bertrand Thirion (IPMI (2), 2025)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Ambroise Odonnat; Thomas Moreau 001; Alexandre Gramfort; Rémi Flamary (Trans. Mach. Learn. Res., 2025)

PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Alexandre Gramfort (CoRR, 2025)

SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges. - Ce Ju; Reinmar J. Kobler; Antoine Collas; Motoaki Kawanabe; Cuntai Guan; Bertrand Thirion (CoRR, 2025)

Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry. - Antoine Collas; Ce Ju; Nicolas Salvy; Bertrand Thirion (CoRR, 2025)