Tavenard, Romain

11 publications

NeurIPS 2025 Differentiable Generalized Sliced Wasserstein Plans Laetitia Chapel, Romain Tavenard, Samuel Vaiter
ICLR 2025 One for All and All for One: Efficient Computation of Partial Wasserstein Distances on the Line Laetitia Chapel, Romain Tavenard
ECML-PKDD 2023 Match-and-Deform: Time Series Domain Adaptation Through Optimal Transport and Temporal Alignment François Painblanc, Laetitia Chapel, Nicolas Courty, Chloé Friguet, Charlotte Pelletier, Romain Tavenard
MLJ 2023 Scalable Clustering of Segmented Trajectories Within a Continuous Time Framework: Application to Maritime Traffic Data Pierre Gloaguen, Laetitia Chapel, Chloé Friguet, Romain Tavenard
TMLR 2022 Time Series Alignment with Global Invariances Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard
MLOSS 2021 POT: Python Optimal Transport 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
MLOSS 2020 Tslearn, a Machine Learning Toolkit for Time Series Data Romain Tavenard, Johann Faouzi, Gilles Vandewiele, Felix Divo, Guillaume Androz, Chester Holtz, Marie Payne, Roman Yurchak, Marc Rußwurm, Kushal Kolar, Eli Woods
ICML 2019 Optimal Transport for Structured Data with Application on Graphs Vayer Titouan, Nicolas Courty, Romain Tavenard, Chapel Laetitia, Rémi Flamary
NeurIPS 2019 Sliced Gromov-Wasserstein Vayer Titouan, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel
ECML-PKDD 2017 Efficient Temporal Kernels Between Feature Sets for Time Series Classification Romain Tavenard, Simon Malinowski, Laetitia Chapel, Adeline Bailly, Heider Sanchez, Benjamin Bustos
ECML-PKDD 2016 Cost-Aware Early Classification of Time Series Romain Tavenard, Simon Malinowski