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Titouan Vayer
Titouan Vayer
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Title
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Cited by
Year
Pot: Python optimal transport
R Flamary, N Courty, A Gramfort, MZ Alaya, A Boisbunon, S Chambon, ...
Journal of Machine Learning Research 22 (78), 1-8, 2021
7512021
Optimal Transport for structured data with application on graphs
V Titouan, N Courty, R Tavenard, C Laetitia, R Flamary
International Conference on Machine Learning (ICML), 6275-6284, 2019
280*2019
Fused Gromov-Wasserstein distance for structured objects
T Vayer, L Chapel, R Flamary, R Tavenard, N Courty
Algorithms 13 (9), 212, 2020
109*2020
Sliced gromov-wasserstein
V Titouan, R Flamary, N Courty, R Tavenard
Neural Information Processing Systems (NeurIPS) 32, 2019
1092019
CO-Optimal Transport
V Titouan, I Redko, R Flamary, N Courty
Neural Information Processing Systems (NeurIPS) 33, 2020
71*2020
Online Graph Dictionary Learning
C Vincent-Cuaz, T Vayer, R Flamary, M Corneli, N Courty
International Conference on Machine Learning (ICML), 10564-10574, 2021
522021
Semi-relaxed Gromov Wasserstein divergence with applications on graphs
C Vincent-Cuaz, R Flamary, M Corneli, T Vayer, N Courty
International Conference on Learning Representations (ICLR), 2022
392022
Template based Graph Neural Network with Optimal Transport Distances
C Vincent-Cuaz, R Flamary, M Corneli, T Vayer, N Courty
Neural Information Processing Systems (NeurIPS), 2022
242022
A contribution to Optimal Transport on incomparable spaces
T Vayer
Université Bretagne Sud, 2020
242020
Time series alignment with global invariances
T Vayer, R Tavenard, L Chapel, N Courty, R Flamary, Y Soullard
Transactions on Machine Learning Research, 2022
122022
Controlling Wasserstein distances by Kernel norms with application to Compressive Statistical Learning
T Vayer, R Gribonval
Journal of Machine Learning Research 24 (149), 1--51, 2023
82023
Subspace detours meet gromov–wasserstein
C Bonet, T Vayer, N Courty, F Septier, L Drumetz
Algorithms 14 (12), 366, 2021
72021
Fast multiscale diffusion on graphs
S Marcotte, A Barbe, R Gribonval, T Vayer, M Sebban, P Borgnat, ...
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
5*2022
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein
H Van Assel, C Vincent-Cuaz, T Vayer, R Flamary, N Courty
arXiv preprint arXiv:2310.03398, 2023
42023
Learning graphical factor models with riemannian optimization
A Hippert-Ferrer, F Bouchard, A Mian, T Vayer, A Breloy
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
42023
Entropic Wasserstein component analysis
A Collas, T Vayer, R Flamary, A Breloy
2023 IEEE 33rd International Workshop on Machine Learning for Signal …, 2023
42023
Snekhorn: Dimension reduction with symmetric entropic affinities
H Van Assel, T Vayer, R Flamary, N Courty
Advances in Neural Information Processing Systems 36, 2024
32024
Semi-relaxed Gromov-Wasserstein divergence for graphs classification
C Vincent-Cuaz, R Flamary, M Corneli, T Vayer, N Courty
Colloque GRETSI 2022-XXVIIIème Colloque Francophone de Traitement du Signal …, 2022
22022
Optimization of the diffusion time in graph diffused-wasserstein distances: Application to domain adaptation
A Barbe, P Gonçalves, M Sebban, P Borgnat, R Gribonval, T Vayer
2021 IEEE 33rd International Conference on Tools with Artificial …, 2021
22021
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection
H Van Assel, C Vincent-Cuaz, N Courty, R Flamary, P Frossard, T Vayer
arXiv preprint arXiv:2402.02239, 2024
12024
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Articles 1–20