Titouan Vayer
Publications
Publications
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Schur's Positive-Definite Network: Deep Learning in the SPD cone with structureInternational Conference on Learning Representations ICLR 2025, Apr 2025, Singapore, Singapore |
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Bridging Arbitrary and Tree Metrics via Differentiable Gromov HyperbolicityNeurIPS 2025 - 39th Annual Conference on Neural Information Processing Systems, Dec 2025, San diego (Californie), United States |
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En quête de précision : Un benchmark open-source et un solveur polyvalent pour le Graphical LassoGRETSI 2025 - XXXème Colloque Francophone de Traitement du Signal et des Images, Aug 2025, Strasboug, France. pp.1-3 |
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Optimal Transport with Adaptive RegularisationNeurIPS OTML Workshop, Dec 2023, New Orleans, France |
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Interpolating between Clustering and Dimensionality Reduction with Gromov-WassersteinNeurIPS OTML Workshop, Dec 2023, New Orleans, United States |
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Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical LassoGRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble (France), France. pp.1-4 |
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SNEkhorn: Dimension Reduction with Symmetric Entropic AffinitiesThirty-seventh Annual Conference on Neural Information Processing Systems (NeurIPS), Dec 2023, New Orleans, United States |
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Learning Graphical Factor Models with Riemannian OptimizationJoint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2023), Sep 2023, Torino, Italy. ⟨10.1007/978-3-031-43421-1_21⟩ |
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Entropic Wasserstein component analysisIEEE International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2023, Rome, Italy |
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Optimisation Riemannienne pour l'apprentissage de graphes structurésGRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France. pp.585-588 |
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Template based Graph Neural Network with Optimal Transport DistancesNeurIPS 2022 – 36th Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States |
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Semi-relaxed Gromov-Wasserstein divergence for graphs classificationColloque GRETSI 2022 - XXVIIIème Colloque Francophone de Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Semi-relaxed Gromov Wasserstein divergence with applications on graphsICLR 2022 - 10th International Conference on Learning Representations, Apr 2022, Virtual, France. pp.1-28 |
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Fast Multiscale Diffusion on GraphsICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapore, Singapore. ⟨10.1109/ICASSP43922.2022.9746802⟩ |
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Online Graph Dictionary LearningICML 2021 - 38th International Conference on Machine Learning, Jul 2021, Virtual Conference, United States. ⟨10.48550/arXiv.2102.06555⟩ |
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Optimization of the Diffusion Time in Graph Diffused-Wasserstein Distances: Application to Domain AdaptationICTAI 2021 - 33rd IEEE International Conference on Tools with Artificial Intelligence, Nov 2021, Virtual conference, France. pp.1-8, ⟨10.1109/ICTAI52525.2021.00125⟩ |
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CO-Optimal TransportNeural Information Processing Systems (NeurIPS), Dec 2020, Online, Canada |
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Optimal Transport for structured data with application on graphsICML 2019 - 36th International Conference on Machine Learning, Jun 2019, Long Beach, United States. pp.1-16 |
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Sliced Gromov-WassersteinNeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada |
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Path-conditioned training: a principled way to rescale ReLU neural networks2026 |
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On sparsity, extremal structure, and monotonicity properties of Wasserstein and Gromov-Wasserstein optimal transport plans2026 |
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A note on the relations between mixture models, maximum-likelihood and entropic optimal transport2025 |
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Compressive Recovery of Sparse Precision Matrices2023 |
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Semi-relaxed Gromov Wasserstein divergence with applications on graphs2021 |
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Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties2019 |
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Une contribution au transport optimal sur des espaces incomparablesOptimization and Control [math.OC]. Université de Bretagne Sud, 2020. English. ⟨NNT : 2020LORIS576⟩ |
PASCOLogiciel hal-05086352v1 |
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Code for reproducible research - Fast Multiscale Diffusion on Graphs2022 |