The Bures Metric for Generative Adversarial Networks-Reference-Cited by-同舟云学术

The Bures Metric for Generative Adversarial Networks

Published:2021 Issue: Volume: Page:52-66
ISSN:0302-9743
Container-title:Machine Learning and Knowledge Discovery in Databases. Research Track
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Author:

De Meulemeester Hannes^ORCID,Schreurs Joachim^ORCID,Fanuel Michaël^ORCID,De Moor Bart^ORCID,Suykens Johan A. K.^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-86520-7_4

Reference39 articles.

1. Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: Proceedings of the 34th International Conference on Machine Learning (ICML) (2017)

2. Bhatia, R., Jain, T., Lim, Y.: On the Bures-Wasserstein distance between positive definite matrices. Expositiones Mathematicae 37(2), 165–191 (2019)

3. Binkowski, M., Sutherland, D.J., Arbel, M., Gretton, A.: Demystifying MMD GANs. In: Proceedings of the International Conference on Learning Representations (ICLR) (2018)

4. Che, T., Li, Y., Jacob, A.P., Bengio, Y., Li, W.: Mode regularized generative adversarial networks. In: Proceedings of the International Conference on Learning Representations (ICLR) (2017)

5. Dieng, A.B., Ruiz, F.J.R., Blei, D.M., Titsias, M.K.: Prescribed generative adversarial networks. arxiv:1910.04302 (2020)

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