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...
Saved in:
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: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/155575 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Convergence of non-convex non-concave GANs using sinkhorn divergence
by: Adnan, Risman, et al.
Published: (2022) -
Cascade EF-GAN : progressive facial expression editing with local focuses
by: Wu, Rongliang, et al.
Published: (2021) -
Augmenting image data using generative adversarial networks (GAN)
by: Liu, Xinchi
Published: (2024) -
extendGAN+: transferable data augmentation framework using WGAN-GP for data-driven indoor localisation model
by: Yean, Seanglidet, et al.
Published: (2023) -
Lightweight privacy-preserving GAN framework for model training and image synthesis
by: YANG, Yang, et al.
Published: (2022)