Hv0nnus/Sampled-Gromov-Wasserstein
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The informations needed to understand the code are in the Sampled Gromov Wasserstein notebook. - This notebook summarises the code of the paper Sampled Gromov Wasserstein accepted at the Journal Track of ECML-PKDD 2021 and allows to reproduce every tables and figures in the paper and in the supplementary material. An open source version is available at https://hal.archives-ouvertes.fr/hal-03232509/document. - To allow further reuse, we plan to integrate it into the **POT library** (https://pythonot.github.io/) very soon, check the latest POT library version if you want to use the algorithm and do not care about reproducing the experiments of this paper. - Do not hesitate to send a mail if you have any questions about the code or the paper : tanguy.kerdoncuff@laposte.net
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