Learning GANs in simultaneous game using Sinkhorn with positive features

Learning GANs in simultaneous game using Sinkhorn with positive features

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

Internet

https://hdl.handle.net/10356/155575

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