Titouan Vayer

Orcid: 0000-0002-8115-572X

According to our database1, Titouan Vayer authored at least 27 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure.
CoRR, 2024

Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection.
CoRR, 2024

2023
Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning.
J. Mach. Learn. Res., 2023

Compressive Recovery of Sparse Precision Matrices.
CoRR, 2023

Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein.
CoRR, 2023

Optimal Transport with Adaptive Regularisation.
CoRR, 2023

Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso.
CoRR, 2023

Learning Graphical Factor Models with Riemannian Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Entropic Wasserstein Component Analysis.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

2022
Time Series Alignment with Global Invariances.
Trans. Mach. Learn. Res., 2022

Template based Graph Neural Network with Optimal Transport Distances.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Semi-relaxed Gromov-Wasserstein divergence and applications on graphs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Fast Multiscale Diffusion On Graphs.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
POT: Python Optimal Transport.
J. Mach. Learn. Res., 2021

Semi-relaxed Gromov Wasserstein divergence with applications on graphs.
CoRR, 2021

Subspace Detours Meet Gromov-Wasserstein.
Algorithms, 2021

Optimization of the Diffusion Time in Graph Diffused-Wasserstein Distances: Application to Domain Adaptation.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Online Graph Dictionary Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
A contribution to Optimal Transport on incomparable spaces. (Une contribution au Transport Optimal sur des espaces incomparables).
PhD thesis, 2020

A contribution to Optimal Transport on incomparable spaces.
CoRR, 2020

Fused Gromov-Wasserstein Distance for Structured Objects.
Algorithms, 2020

CO-Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Sliced Gromov-Wasserstein.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimal Transport for structured data with application on graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties.
CoRR, 2018

Optimal Transport for structured data.
CoRR, 2018


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