What is recorded here?
Combined scalable conditional GAN architectural/training changes with generator orthogonal regularization and a truncation-based control of image fidelity versus variety.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
GANs and orthogonal regularization have predecessors. Truncation deliberately trades distribution coverage for fidelity, and large-scale training instability is not universally solved. Original2018 preprint and ICLR2019 publication are distinct.
Read the original work
- Large Scale GAN Training for High Fidelity Natural Image Synthesis
- Brock et al.: BigGAN scalable training and truncation control — author/institutional project
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People and systems
Andrew Brock; Jeff Donahue; Karen Simonyan
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Brock et al.: BigGAN scalable training and truncation control
Combined scalable conditional GAN architectural/training changes with generator orthogonal regularization and a truncation-based control of image fidelity versus variety.
Scientific scope
GANs and orthogonal regularization have predecessors. Truncation deliberately trades distribution coverage for fidelity, and large-scale training instability is not universally solved. Original2018 preprint and ICLR2019 publication are distinct.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Andrew Brock; Jeff Donahue; Karen Simonyan
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.