Graph Diffusion Wasserstein Distances-Reference-Cited by-同舟云学术

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Graph Diffusion Wasserstein Distances

Published:2021 Issue: Volume: Page:577-592
ISSN:0302-9743
Container-title:Machine Learning and Knowledge Discovery in Databases
language:
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Author:

Barbe Amélie,Sebban Marc,Gonçalves Paulo,Borgnat Pierre,Gribonval Rémi

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67661-2_34

Reference24 articles.

1. Al-Mohy, A., Higham, N.: Computing the action of the matrix exponential, with an application to exponential integrators. SIAM J. Sci. Comp. 33(2), 488–511 (2011)

2. Bruzzone, L., Marconcini, M.: Domain adaptation problems: a DASVM classification technique and a circular validation strategy. IEEE Trans. Pattern Anal. Mach. Intell. 32(5), 770–787 (2010)

3. Chung, F.: The heat kernel as the pagerank of a graph. Proc. Nat. Acad. Sci. 104(50), 19735–19740 (2007)

4. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);N Courty,2014

5. Courty, N., Flamary, R., Tuia, D., Rakotomamonjy, A.: Optimal transport for domain adaptation. Trans. Pattern Anal. Mach. Intell. 39(9), 1853–1865 (2017)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Wasserstein-Based Graph Alignment;IEEE Transactions on Signal and Information Processing over Networks;2022

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