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ORCIDAntoine Collas
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2020 – today
- 2025
[j5]Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary:
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. Trans. Mach. Learn. Res. 2025 (2025)- [c7]Joseph Paillard, Antoine Collas, Denis A. Engemann, Bertrand Thirion:
Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction. IPMI (2) 2025: 79-93 - [i14]Théo Gnassounou, Antoine Collas, Rémi Flamary, Alexandre Gramfort:
PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. CoRR abs/2503.04582 (2025) - [i13]Ce Ju, Reinmar J. Kobler, Antoine Collas, Motoaki Kawanabe, Cuntai Guan, Bertrand Thirion:
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges. CoRR abs/2504.18882 (2025) - [i12]Antoine Collas, Ce Ju, Nicolas Salvy, Bertrand Thirion:
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry. CoRR abs/2505.18193 (2025) - [i11]Joseph Paillard, Antoine Collas, Denis A. Engemann, Bertrand Thirion:
Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction. CoRR abs/2508.08724 (2025) - 2024
- [c6]Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort:
Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. EUSIPCO 2024: 1367-1371 - [c5]Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann:
Geodesic Optimization for Predictive Shift Adaptation on EEG data. NeurIPS 2024 - [i10]Antoine Collas, Rémi Flamary, Alexandre Gramfort:
Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. CoRR abs/2402.03345 (2024) - [i9]Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort:
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. CoRR abs/2403.15415 (2024) - [i8]Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann:
Geodesic Optimization for Predictive Shift Adaptation on EEG data. CoRR abs/2407.03878 (2024) - [i7]Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary:
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. CoRR abs/2407.11676 (2024) - [i6]Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort:
Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. CoRR abs/2407.14303 (2024) - 2023
- [j4]Alice Le Brigant
, Jules Deschamps, Antoine Collas, Nina Miolane:
Parametric Information Geometry with the Package Geomstats. ACM Trans. Math. Softw. 49(4): 34:1-34:26 (2023) - [j3]Antoine Collas, Arnaud Breloy, Chengfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez:
Riemannian Optimization for Non-Centered Mixture of Scaled Gaussian Distributions. IEEE Trans. Signal Process. 71: 2475-2490 (2023) - [c4]Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy:
Entropic Wasserstein Component Analysis. MLSP 2023: 1-6 - [i5]Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy:
Entropic Wasserstein Component Analysis. CoRR abs/2303.05119 (2023) - [i4]Florent Bouchard, Arnaud Breloy, Antoine Collas, Alexandre Renaux, Guillaume Ginolhac:
The Fisher-Rao geometry of CES distributions. CoRR abs/2310.01032 (2023) - 2022
- [b1]Antoine Collas:
Géométrie riemannienne pour l'estimation et l'apprentissage statistiques : application à la télédétection. (Riemannian geometry for statistical estimation and learning : application to remote sensing). University of Paris-Saclay, France, 2022 - [c3]Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez:
Robust Geometric Metric Learning. EUSIPCO 2022: 1447-1451 - [c2]Antoine Collas, Florent Bouchard, Guillaume Ginolhac, Arnaud Breloy, Chengfang Ren, Jean Philippe Ovarlez:
On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems. ICASSP 2022: 5697-5701 - [i3]Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez:
Robust Geometric Metric Learning. CoRR abs/2202.11550 (2022) - [i2]Antoine Collas, Arnaud Breloy, Chengfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez:
Riemannian optimization for non-centered mixture of scaled Gaussian distributions. CoRR abs/2209.03315 (2022) - [i1]Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane:
Parametric information geometry with the package Geomstats. CoRR abs/2211.11643 (2022) - 2021
- [j2]Antoine Collas, Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez:
Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering. IEEE Trans. Signal Process. 69: 6546-6560 (2021) - [c1]Antoine Collas, Florent Bouchard, Arnaud Breloy, Chenfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez:
A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization. ICASSP 2021: 5160-5164 - 2020
- [j1]Ammar Mian, Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Jean Philippe Ovarlez:
Robust Low-Rank Change Detection for Multivariate SAR Image Time Series. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 3545-3556 (2020)
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