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ORCIDQuentin Barthélemy
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2020 – today
- 2024
[c15]Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen:
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. ICLR 2024- [i9]Blaise Delattre, Quentin Barthélemy, Alexandre Allauzen:
Spectral Norm of Convolutional Layers with Circular and Zero Paddings. CoRR abs/2402.00240 (2024) - 2023
- [c14]Blaise Delattre, Quentin Barthélemy, Alexandre Araujo, Alexandre Allauzen:
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. ICML 2023: 7513-7532 - [c13]Devashish Lohani, Carlos Fernando Crispim Junior, Quentin Barthélemy, Sarah Bertrand, Lionel Robinault, Laure Tougne Rodet:
Leveraging Unsupervised and Self-Supervised Learning for Video Anomaly Detection. VISIGRAPP (5: VISAPP) 2023: 132-143 - [i8]Blaise Delattre, Quentin Barthélemy, Alexandre Araujo, Alexandre Allauzen:
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. CoRR abs/2305.16173 (2023) - [i7]Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen:
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. CoRR abs/2309.16883 (2023) - 2022
- [j8]Devashish Lohani
, Carlos Fernando Crispim Junior, Quentin Barthélemy, Sarah Bertrand, Lionel Robinault, Laure Tougne:
Perimeter Intrusion Detection by Video Surveillance: A Survey. Sensors 22(9): 3601 (2022) - [c12]Devashish Lohani, Carlos Fernando Crispim Junior, Quentin Barthélemy, Sarah Bertrand, Lionel Robinault, Laure Tougne Rodet:
Unsupervised and Adaptive Perimeter Intrusion Detector. ICIP 2022: 3621-3625 - [d1]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, Maria Sayu Yamamoto, Pierre Clisson, Marie-Constance Corsi:
pyRiemann/pyRiemann: v0.3. Zenodo, 2022
- [i6]Quentin Barthélemy, Sylvain Chevallier, Raphaëlle Bertrand-Lalo, Pierre Clisson:
End-to-end P300 BCI using Bayesian accumulation of Riemannian probabilities. CoRR abs/2203.07807 (2022) - 2021
- [j7]Sylvain Chevallier, Emmanuel K. Kalunga, Quentin Barthélemy, Éric Monacelli:
Review of Riemannian Distances and Divergences, Applied to SSVEP-based BCI. Neuroinformatics 19(1): 93-106 (2021) - [c11]Salim Khazem, Sylvain Chevallier, Quentin Barthélemy, Karim Haroun, Camille Noûs:
Minimizing Subject-dependent Calibration for BCI with Riemannian Transfer Learning. NER 2021: 523-526 - [c10]Devashish Lohani, Carlos Fernando Crispim Junior, Quentin Barthélemy, Sarah Bertrand, Lionel Robinault, Laure Tougne:
Spatio-Temporal Convolutional Autoencoders for Perimeter Intrusion Detection. RRPR 2021: 47-65 - [i5]Salim Khazem, Sylvain Chevallier, Quentin Barthélemy, Karim Haroun, Camille Noûs:
Minimizing subject-dependent calibration for BCI with Riemannian transfer learning. CoRR abs/2111.12071 (2021) - 2020
- [c9]Florian Yger, Sylvain Chevallier, Quentin Barthélemy, Suvrit Sra:
Geodesically-convex optimization for averaging partially observed covariance matrices. ACML 2020: 417-432
2010 – 2019
- 2018
- [c8]Emmanuel K. Kalunga, Sylvain Chevallier, Quentin Barthélemy:
Transfer Learning for SSVEP-based BCI Using Riemannian Similarities Between Users. EUSIPCO 2018: 1685-1689 - 2017
- [j6]Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif:
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. Signal Process. 130: 389-402 (2017) - 2016
- [j5]Emmanuel K. Kalunga, Sylvain Chevallier, Quentin Barthélemy, Karim Djouani, Éric Monacelli, Yskandar Hamam:
Online SSVEP-based BCI using Riemannian geometry. Neurocomputing 191: 55-68 (2016) - [i4]Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif:
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. CoRR abs/1609.09525 (2016) - 2015
- [j4]Quentin Barthélemy, Anthony Larue, Jérôme I. Mars:
Color Sparse Representations for Image Processing: Review, Models, and Prospects. IEEE Trans. Image Process. 24(11): 3978-3989 (2015) - [c7]Emmanuel K. Kalunga, Sylvain Chevallier, Quentin Barthélemy, Karim Djouani, Yskandar Hamam, Éric Monacelli:
From Euclidean to Riemannian Means: Information Geometry for SSVEP Classification. GSI 2015: 595-604 - 2014
- [j3]Quentin Barthélemy, Anthony Larue, Jérôme I. Mars:
Decomposition and dictionary learning for 3D trajectories. Signal Process. 98: 423-437 (2014) - [j2]Quentin Barthélemy, Anthony Larue, Jérôme I. Mars:
About QLMS Derivations. IEEE Signal Process. Lett. 21(2): 240-243 (2014) - [c6]Sylvain Chevallier, Quentin Barthélemy, Jamal Atif:
On the need for metrics in dictionary learning assessment. EUSIPCO 2014: 1427-1431 - [c5]Sylvain Chevallier, Quentin Barthélemy, Jamal Atif:
Subspace metrics for multivariate dictionaries and application to EEG. ICASSP 2014: 7178-7182 - 2013
- [c4]Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag:
Multi-dimensional sparse structured signal approximation using split bregman iterations. ICASSP 2013: 3826-3830 - [i3]Sylvain Chevallier, Quentin Barthélemy, Jamal Atif:
Metrics for Multivariate Dictionaries. CoRR abs/1302.4242 (2013) - [i2]Quentin Barthélemy, Cédric Gouy-Pailler, Yoann Isaac, Antoine Souloumiac, Anthony Larue, Jérôme I. Mars:
Multivariate Temporal Dictionary Learning for EEG. CoRR abs/1303.0742 (2013) - [i1]Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag:
Multi-dimensional sparse structured signal approximation using split Bregman iterations. CoRR abs/1303.5197 (2013) - 2012
- [j1]Quentin Barthélemy, Anthony Larue, Aurélien Mayoue, David Mercier, Jérôme I. Mars:
Shift & 2D Rotation Invariant Sparse Coding for Multivariate Signals. IEEE Trans. Signal Process. 60(4): 1597-1611 (2012) - [c3]Quentin Barthélemy, Anthony Larue, Jérôme I. Mars:
3D Rotation Invariant Decomposition of Motion Signals. ECCV Workshops (3) 2012: 172-182 - [c2]Anthony Mouraud, Quentin Barthélemy, Aurélien Mayoue, Cédric Gouy-Pailler, Anthony Larue, Hélène Paugam-Moisy:
From neuronal cost-based metrics towards sparse coded signals classification. ESANN 2012 - [c1]Aurélien Mayoue, Quentin Barthélemy, S. Onis, Anthony Larue:
Preprocessing for classification of sparse data: Application to trajectory recognition. SSP 2012: 37-40
Coauthor Index
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