3D Rotation Invariant Decomposition of Motion Signals. - Quentin Barthélemy; Anthony Larue; Jérôme I. Mars (ECCV Workshops (3), 2012)

From neuronal cost-based metrics towards sparse coded signals classification. - Anthony Mouraud; Quentin Barthélemy; Aurélien Mayoue; Cédric Gouy-Pailler; Anthony Larue; Hélène Paugam-Moisy (ESANN, 2012)

Preprocessing for classification of sparse data: Application to trajectory recognition. - Aurélien Mayoue; Quentin Barthélemy; S. Onis; Anthony Larue (SSP, 2012)

Shift & 2D Rotation Invariant Sparse Coding for Multivariate Signals. - Quentin Barthélemy; Anthony Larue; Aurélien Mayoue; David Mercier; Jérôme I. Mars (IEEE Trans. Signal Process., 2012)

Multi-dimensional sparse structured signal approximation using split bregman iterations. - Yoann Isaac; Quentin Barthélemy; Jamal Atif; Cédric Gouy-Pailler; Michèle Sebag (ICASSP, 2013)

Metrics for Multivariate Dictionaries - Sylvain Chevallier; Quentin Barthélemy; Jamal Atif (CoRR, 2013)

Multivariate Temporal Dictionary Learning for EEG - Quentin Barthélemy; Cédric Gouy-Pailler; Yoann Isaac; Antoine Souloumiac; Anthony Larue; Jérôme I. Mars (CoRR, 2013)

On the need for metrics in dictionary learning assessment. - Sylvain Chevallier; Quentin Barthélemy; Jamal Atif (EUSIPCO, 2014)

Subspace metrics for multivariate dictionaries and application to EEG. - Sylvain Chevallier; Quentin Barthélemy; Jamal Atif (ICASSP, 2014)

Decomposition and dictionary learning for 3D trajectories. - Quentin Barthélemy; Anthony Larue; Jérôme I. Mars (Signal Process., 2014)

About QLMS Derivations. - Quentin Barthélemy; Anthony Larue; Jérôme I. Mars (IEEE Signal Process. Lett., 2014)

From Euclidean to Riemannian Means: Information Geometry for SSVEP Classification. - Emmanuel K. Kalunga; Sylvain Chevallier; Quentin Barthélemy; Karim Djouani; Yskandar Hamam; Éric Monacelli (GSI, 2015)

Color Sparse Representations for Image Processing: Review, Models, and Prospects. - Quentin Barthélemy; Anthony Larue; Jérôme I. Mars (IEEE Trans. Image Process., 2015)

Online SSVEP-based BCI using Riemannian geometry. - Emmanuel K. Kalunga; Sylvain Chevallier; Quentin Barthélemy; Karim Djouani; Éric Monacelli; Yskandar Hamam (Neurocomputing, 2016)

Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. - Yoann Isaac; Quentin Barthélemy; Cédric Gouy-Pailler; Michèle Sebag; Jamal Atif (Signal Process., 2017)

Transfer Learning for SSVEP-based BCI Using Riemannian Similarities Between Users. - Emmanuel K. Kalunga; Sylvain Chevallier; Quentin Barthélemy (EUSIPCO, 2018)

Geodesically-convex optimization for averaging partially observed covariance matrices. - Florian Yger; Sylvain Chevallier; Quentin Barthélemy; Suvrit Sra (ACML, 2020)

Minimizing Subject-dependent Calibration for BCI with Riemannian Transfer Learning. - Salim Khazem; Sylvain Chevallier; Quentin Barthélemy; Karim Haroun; Camille Noûs (NER, 2021)

Spatio-Temporal Convolutional Autoencoders for Perimeter Intrusion Detection. - Devashish Lohani; Carlos Fernando Crispim Junior; Quentin Barthélemy; Sarah Bertrand; Lionel Robinault; Laure Tougne (RRPR, 2021)

Review of Riemannian Distances and Divergences, Applied to SSVEP-based BCI. - Sylvain Chevallier; Emmanuel K. Kalunga; Quentin Barthélemy; Éric Monacelli (Neuroinformatics, 2021)

Unsupervised and Adaptive Perimeter Intrusion Detector. - Devashish Lohani; Carlos Fernando Crispim Junior; Quentin Barthélemy; Sarah Bertrand; Lionel Robinault; Laure Tougne Rodet (ICIP, 2022)

End-to-end P300 BCI using Bayesian accumulation of Riemannian probabilities. - Quentin Barthélemy; Sylvain Chevallier; Raphaëlle Bertrand-Lalo; Pierre Clisson (CoRR, 2022)

Perimeter Intrusion Detection by Video Surveillance: A Survey. - Devashish Lohani; Carlos Fernando Crispim Junior; Quentin Barthélemy; Sarah Bertrand; Lionel Robinault; Laure Tougne (Sensors, 2022)

pyRiemann/pyRiemann: v0.3. - Alexandre Barachant; Quentin Barthélemy; Jean-Rémi King; Alexandre Gramfort; Sylvain Chevallier; Pedro L. C. Rodrigues; Emanuele Olivetti; Vladislav Goncharenko; Gabriel Wagner vom Berg; Ghiles Reguig; Arthur Lebeurrier; Erik Bjäreholt; et al. (Zenodo, 2022)

Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. - Blaise Delattre; Quentin Barthélemy; Alexandre Araujo; Alexandre Allauzen (ICML, 2023)

Leveraging Unsupervised and Self-Supervised Learning for Video Anomaly Detection. - Devashish Lohani; Carlos Fernando Crispim Junior; Quentin Barthélemy; Sarah Bertrand; Lionel Robinault; Laure Tougne Rodet (VISIGRAPP (5: VISAPP), 2023)

The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. - Blaise Delattre; Alexandre Araujo; Quentin Barthélemy; Alexandre Allauzen (ICLR, 2024)

Spectral Norm of Convolutional Layers with Circular and Zero Paddings. - Blaise Delattre; Quentin Barthélemy; Alexandre Allauzen (CoRR, 2024)

Bridging the Theoretical Gap in Randomized Smoothing. - Blaise Delattre; Paul Caillon; Quentin Barthélemy; Erwan Fagnou; Alexandre Allauzen (AISTATS, 2025)

Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks. - Jérémy Scanvic; Quentin Barthélemy; Julián Tachella (CoRR, 2025)