Learning GANs in simultaneous game using Sinkhorn with positive features

Learning GANs in simultaneous game using Sinkhorn with positive features

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Entropy regularized optimal transport (EOT) distance and its symmetric normalization, known as the Sinkhorn divergence, offer smooth and continuous metrized weak-convergence distance metrics. They have excellent geometric properties and are useful to compare probability distributions in some generat...

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Bibliographic Details
Main Authors: Risman Adnan, Muchlisin Adi Saputra, Junaidillah Fadlil, Ezerman, Martianus Frederic, Muhamad Iqbal, Tjan Basaruddin
Other Authors: School of Physical and Mathematical Sciences
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Generative Adversarial Network
Entropy Regularized Optimal Transport
Online Access:https://hdl.handle.net/10356/155575

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