Learning to Generate Wasserstein Barycenters

Learning to Generate Wasserstein Barycenters

Journal of Mathematical Imaging and Vision (JMIV), 2021

24 February 2021

Nicolas Bonneel

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Papers citing "Learning to Generate Wasserstein Barycenters"

7 / 7 papers shown

Title
Estimating Barycenters of Distributions with Neural Optimal TransportInternational Conference on Machine Learning (ICML), 2024 Alexander Kolesov Petr Mokrov Igor Udovichenko Milena Gazdieva G. Pammer Evgeny Burnaev Alexander Korotin OT 268 10 0 06 Feb 2024
Scalable Optimal Transport Methods in Machine Learning: A Contemporary SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Abdelwahed Khamis Russell Tsuchida Mohamed Tarek V. Rolland Lars Petersson OT 359 29 0 08 May 2023
Beckman Defense A. V. Subramanyam OOD AAML 251 0 0 04 Jan 2023
GeONet: a neural operator for learning the Wasserstein geodesicConference on Uncertainty in Artificial Intelligence (UAI), 2022 Andrew Gracyk Xiaohui Chen OT 312 2 0 28 Sep 2022
Meta Optimal TransportInternational Conference on Machine Learning (ICML), 2022 Brandon Amos Samuel N. Cohen Giulia Luise I. Redko OT 275 27 0 10 Jun 2022
Wasserstein Iterative Networks for Barycenter EstimationNeural Information Processing Systems (NeurIPS), 2022 Alexander Korotin Vage Egiazarian Lingxiao Li Evgeny Burnaev 287 32 0 28 Jan 2022
Bayesian Learning with Wasserstein Barycenters Julio D. Backhoff Veraguas J. Fontbona Gonzalo Rios Felipe A. Tobar 256 36 0 28 May 2018