Antoine Collas

28 papers A* 1Misc 2Journal 20Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization. CoRR Bruno Aristimunha, Ce Ju, Antoine Collas, Florent Bouchard, Ammar Mian, Bertrand Thirion, Sylvain Chevallier, Reinmar J. Kobler
2025	—	`conf`	Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction. IPMI (2) Joseph Paillard, Antoine Collas, Denis A. Engemann, Bertrand Thirion
2025	J	`jnl`	Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction. CoRR Joseph Paillard, Antoine Collas, Denis A. Engemann, Bertrand Thirion
2025	J	`jnl`	PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. CoRR Théo Gnassounou, Antoine Collas, Rémi Flamary, Alexandre Gramfort
2025	J	`jnl`	Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry. CoRR Antoine Collas, Ce Ju, Nicolas Salvy, Bertrand Thirion
2025	J	`jnl`	SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. Trans. Mach. Learn. Res. Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary
2025	J	`jnl`	SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges. CoRR Ce Ju, Reinmar J. Kobler, Antoine Collas, Motoaki Kawanabe, Cuntai Guan, Bertrand Thirion
2024	A*	`conf`	Geodesic Optimization for Predictive Shift Adaptation on EEG data. NeurIPS Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann
2024	J	`jnl`	Geodesic Optimization for Predictive Shift Adaptation on EEG data. CoRR Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann
2024	J	`jnl`	Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. CoRR Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort
2024	—	`conf`	Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. EUSIPCO Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort
2024	J	`jnl`	Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. CoRR Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort
2024	J	`jnl`	SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. CoRR Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary
2024	J	`jnl`	Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. CoRR Antoine Collas, Rémi Flamary, Alexandre Gramfort
2023	—	`conf`	Entropic Wasserstein Component Analysis. MLSP Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy
2023	J	`jnl`	Entropic Wasserstein Component Analysis. CoRR Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy
2023	J	`jnl`	Parametric Information Geometry with the Package Geomstats. ACM Trans. Math. Softw. Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
2023	J	`jnl`	Riemannian Optimization for Non-Centered Mixture of Scaled Gaussian Distributions. IEEE Trans. Signal Process. Antoine Collas, Arnaud Breloy, Chengfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez
2023	J	`jnl`	The Fisher-Rao geometry of CES distributions. CoRR Florent Bouchard, Arnaud Breloy, Antoine Collas, Alexandre Renaux, Guillaume Ginolhac
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	Misc	`conf`	On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems. ICASSP Antoine Collas, Florent Bouchard, Guillaume Ginolhac, Arnaud Breloy, Chengfang Ren, Jean Philippe Ovarlez
2022	J	`jnl`	Parametric information geometry with the package Geomstats. CoRR Alice Le Brigant, Jules Deschamps, Antoine Collas, Nina Miolane
2022	J	`jnl`	Riemannian optimization for non-centered mixture of scaled Gaussian distributions. CoRR Antoine Collas, Arnaud Breloy, Chengfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez
2022	—	`conf`	Robust Geometric Metric Learning. EUSIPCO Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez
2022	J	`jnl`	Robust Geometric Metric Learning. CoRR Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez
2021	Misc	`conf`	A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization. ICASSP Antoine Collas, Florent Bouchard, Arnaud Breloy, Chenfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez
2021	J	`jnl`	Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering. IEEE Trans. Signal Process. Antoine Collas, Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez
2020	J	`jnl`	Robust Low-Rank Change Detection for Multivariate SAR Image Time Series. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Ammar Mian, Antoine Collas, Arnaud Breloy, Guillaume Ginolhac, Jean Philippe Ovarlez