Titouan Vayer - RankMe

45 papers A* 8B 1Misc 1Journal 32Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On sparsity, extremal structure, and monotonicity properties of Wasserstein and Gromov-Wasserstein optimal transport plans. CoRR Titouan Vayer
2026	J	`jnl`	Path-conditioned training: a principled way to rescale ReLU neural networks. CoRR Arthur Lebeurrier, Titouan Vayer, Rémi Gribonval
2025	J	`jnl`	A note on the relations between mixture models, maximum-likelihood and entropic optimal transport. CoRR Titouan Vayer, Etienne Lasalle
2025	J	`jnl`	Bridging Arbitrary and Tree Metrics via Differentiable Gromov Hyperbolicity. CoRR Pierre Houedry, Nicolas Courty, Florestan Martin-Baillon, Laetitia Chapel, Titouan Vayer
2025	J	`jnl`	Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein. Trans. Mach. Learn. Res. Hugues Van Assel, Cédric Vincent-Cuaz, Nicolas Courty, Rémi Flamary, Pascal Frossard, Titouan Vayer
2025	J	`jnl`	Pasco (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms. Mach. Learn. Etienne Lasalle, Rémi Vaudaine, Titouan Vayer, Pierre Borgnat, Paulo Gonçalves, Rémi Gribonval, Márton Karsai
2025	A*	`conf`	Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure. ICLR Can Pouliquen, Mathurin Massias, Titouan Vayer
2024	J	`jnl`	Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection. CoRR Hugues Van Assel, Cédric Vincent-Cuaz, Nicolas Courty, Rémi Flamary, Pascal Frossard, Titouan Vayer
2024	J	`jnl`	PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms. CoRR Etienne Lasalle, Rémi Vaudaine, Titouan Vayer, Pierre Borgnat, Rémi Gribonval, Paulo Gonçalves, Márton Karsai
2024	J	`jnl`	Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure. CoRR Can Pouliquen, Mathurin Massias, Titouan Vayer
2023	J	`jnl`	Compressive Recovery of Sparse Precision Matrices. CoRR Titouan Vayer, Etienne Lasalle, Rémi Gribonval, Paulo Gonçalves
2023	J	`jnl`	Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning. J. Mach. Learn. Res. Titouan Vayer, Rémi Gribonval
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`	Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso. CoRR Can Pouliquen, Paulo Gonçalves, Mathurin Massias, Titouan Vayer
2023	J	`jnl`	Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein. CoRR Hugues Van Assel, Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Nicolas Courty
2023	—	`conf`	Learning Graphical Factor Models with Riemannian Optimization. ECML/PKDD (4) Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy
2023	J	`jnl`	Optimal Transport with Adaptive Regularisation. CoRR Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty
2023	A*	`conf`	SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. NeurIPS Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty
2023	J	`jnl`	SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. CoRR Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty
2022	Misc	`conf`	Fast Multiscale Diffusion On Graphs. ICASSP Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves
2022	J	`jnl`	Learning Graphical Factor Models with Riemannian Optimization. CoRR Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy
2022	A*	`conf`	Semi-relaxed Gromov-Wasserstein divergence and applications on graphs. ICLR Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
2022	A*	`conf`	Template based Graph Neural Network with Optimal Transport Distances. NeurIPS Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
2022	J	`jnl`	Template based Graph Neural Network with Optimal Transport Distances. CoRR Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
2022	J	`jnl`	Time Series Alignment with Global Invariances. Trans. Mach. Learn. Res. Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard
2021	J	`jnl`	Controlling Wasserstein distances by Kernel norms with application to Compressive Statistical Learning. CoRR Titouan Vayer, Rémi Gribonval
2021	J	`jnl`	Fast Multiscale Diffusion on Graphs. CoRR Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves
2021	A*	`conf`	Online Graph Dictionary Learning. ICML Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty
2021	J	`jnl`	Online Graph Dictionary Learning. CoRR Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty
2021	B	`conf`	Optimization of the Diffusion Time in Graph Diffused-Wasserstein Distances: Application to Domain Adaptation. ICTAI Amélie Barbe, Paulo Gonçalves, Marc Sebban, Pierre Borgnat, Rémi Gribonval, Titouan Vayer
2021	J	`jnl`	POT: Python Optimal Transport. J. Mach. Learn. Res. Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer
2021	J	`jnl`	Semi-relaxed Gromov Wasserstein divergence with applications on graphs. CoRR Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
2021	J	`jnl`	Subspace Detours Meet Gromov-Wasserstein. Algorithms Clément Bonet, Titouan Vayer, Nicolas Courty, François Septier, Lucas Drumetz
2020	J	`jnl`	A contribution to Optimal Transport on incomparable spaces. CoRR Titouan Vayer
2020	—	`—`	A contribution to Optimal Transport on incomparable spaces. (Une contribution au Transport Optimal sur des espaces incomparables). Titouan Vayer
2020	A*	`conf`	CO-Optimal Transport. NeurIPS Titouan Vayer, Ievgen Redko, Rémi Flamary, Nicolas Courty
2020	J	`jnl`	CO-Optimal Transport. CoRR Ievgen Redko, Titouan Vayer, Rémi Flamary, Nicolas Courty
2020	J	`jnl`	Fused Gromov-Wasserstein Distance for Structured Objects. Algorithms Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty
2020	J	`jnl`	Time Series Alignment with Global Invariances. CoRR Titouan Vayer, Laetitia Chapel, Nicolas Courty, Rémi Flamary, Yann Soullard, Romain Tavenard
2019	A*	`conf`	Optimal Transport for structured data with application on graphs. ICML Titouan Vayer, Nicolas Courty, Romain Tavenard, Laetitia Chapel, Rémi Flamary
2019	A*	`conf`	Sliced Gromov-Wasserstein. NeurIPS Titouan Vayer, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel
2019	J	`jnl`	Sliced Gromov-Wasserstein. CoRR Titouan Vayer, Rémi Flamary, Romain Tavenard, Laetitia Chapel, Nicolas Courty
2018	J	`jnl`	Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties. CoRR Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty
2018	J	`jnl`	Optimal Transport for structured data. CoRR Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty