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POT: Python Optimal Transport.

, , , , , , , , , , , , , , , , , , , , , и . J. Mach. Learn. Res., (2021)

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Laetitia Chapel

Laetitia Fellini

Learning and memory processes in mice: a behavioral, molecular and pharmacological study in wild-type and transgenic animals. Uni Bremen, (2009)

Laetitia Boehm

Laetitia Frieling

Laetitia Rimpau

 

Другие публикации лиц с тем же именем

Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning., , и . CoRR, (2020)Optimal Transport for structured data with application on graphs, , , , и . (2018)cite arxiv:1805.09114.Machine learning for structured data. (Apprentissage machine pour données structurées).. (2022)POT: Python Optimal Transport., , , , , , , , , и 12 other автор(ы). J. Mach. Learn. Res., (2021)Hyperbolic Variational Auto-Encoder for Remote Sensing Scene Embeddings., , , и . IGARSS, стр. 5391-5394. IEEE, (2023)Unbalanced Optimal Transport through Non-negative Penalized Linear Regression., , , , и . NeurIPS, стр. 23270-23282. (2021)PerTurbo Manifold Learning Algorithm for Weakly Labeled Hyperspectral Image Classification., , , и . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 7 (4): 1070-1078 (2014)Bridging Arbitrary and Tree Metrics via Differentiable Gromov Hyperbolicity., , , , и . CoRR, (мая 2025)Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections., , , и . TAG-ML, том 221 из Proceedings of Machine Learning Research, стр. 334-370. PMLR, (2023)Sliced Gromov-Wasserstein., , , , и . NeurIPS, стр. 14726-14736. (2019)