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rand_saturation

Syntologyentry name in harvested coderead from the graph 2026-09-24

rand_saturation appears in the code Syntology harvested for 24 papers, as 12 distinct code bodies found in 29 places (a place is one code body under one paper). At least one of them ran in 22 of the papers; 4 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named rand_saturation do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 9 of the 12 distinct code bodies named rand_saturation; 3 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
6ran · our draft was wrong
2ran · fixture could not drive it
1ran
3unverified
4fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 29 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

24 papers shown of 24, newest first; 29 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 2 papers added by Syntology; 3 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
DNF-SR: Dual-Input and Negative-Aware Feature Fine-Tuning for Real-World Image Super-Resolution added by Syntology 2026-09 (from id) SHH-Han/DNF-SR/dinov3_gan/dinov3_convnext_disc.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted no licence file found · pointer only
FedHPro: Federated Hyper-Prototype Learning via Gradient Matching added by Syntology 2026-05 (from id) mala-lab/FedHPro/main_run.py 0d4958248aaee956 ran · our draft was wrong no licence file found · pointer only
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities 18 Oct 2024 haoosz/BiGR/bae/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching 28 May 2024 Yongalls/SelMatch/distill.py 5cb7afb924303755 ran · our draft was wrong no licence file found · pointer only
DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations 23 Jan 2024 mlvlab/DDMI/losses/diffaugment.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution 30 Dec 2023 csslc/ccsr/models/DiffAugment.py db65cf4b9c6f357e ran fingerprinted Apache-2.0 (permissive)
DataDAM: Efficient Dataset Distillation with Attention Matching 29 Sep 2023 datadistillation/datadam/main_DataDAM.py c464d3d7b7e65175 ran · our draft was wrong no licence file found · pointer only
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models 7 Jun 2023 Zhendong-Wang/Diffusion-GAN/diffusion-projected-gan/pg_modules/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation 26 Apr 2023 gnobitab/FuseDream/DiffAugment_pytorch.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Outpainting by Queries 12 Jul 2022 Kaiseem/QueryOTR/models/DiffAug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
Augmentation-Aware Self-Supervision for Data-Efficient GAN Training 31 May 2022 liang-hou/augself-gan/augself-biggan/DiffAugment_pytorch.py 55891b212e588333 unverified MIT (permissive)
SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image 2 Apr 2022 VITA-Group/SinNeRF/models/diff_aug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
CAFE: Learning to Condense Dataset by Aligning Features 3 Mar 2022 kaiwang960112/cafe/distill.py 7f5ed98fe0143f9c ran · our draft was wrong no licence file found · pointer only
Ensembling Off-the-shelf Models for GAN Training 16 Dec 2021 nupurkmr9/vision-aided-gan/vision_aided_loss/DiffAugment_pytorch.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training 1 Nov 2021 identical code first harvested elsewhere abafb0afcfb5d028 ran · our draft was wrong fingerprinted licence of this copy not recorded
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training 1 Nov 2021 postech-cvlab/pytorch-studiogan/src/utils/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted licence not identified · pointer only
Projected GANs Converge Faster 1 Nov 2021 identical code first harvested elsewhere 5b0d8787e670fc63 ran · our draft was wrong fingerprinted licence of this copy not recorded
Generative Adversarial Registration for Improved Conditional Deformable Templates 7 May 2021 neel-dey/Atlas-GAN/src/discriminator_augmentations.py 7af0ab054d5e2a78 unverified MIT (permissive)
Regularizing Generative Adversarial Networks under Limited Data 7 Apr 2021 identical code first harvested elsewhere 5b0d8787e670fc63 ran · our draft was wrong fingerprinted licence of this copy not recorded
Rewriting a Deep Generative Model 30 Jul 2020 PeterWang512/GANSketching/training/networks/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Differentiable Augmentation for Data-Efficient GAN Training 18 Jun 2020 mit-han-lab/data-efficient-gans/DiffAugment_pytorch.py abafb0afcfb5d028 ran · our draft was wrong fingerprinted BSD-2-Clause (permissive)
Differentiable Augmentation for Data-Efficient GAN Training 18 Jun 2020 milmor/LadaGAN-pytorch/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Differentiable Augmentation for Data-Efficient GAN Training 18 Jun 2020 gaborvecsei/SLE-GAN/sle_gan/diff_augment.py fe6b745a5727de14 ran · fixture could not drive it MIT (permissive)
Differentiable Augmentation for Data-Efficient GAN Training 18 Jun 2020 eps696/stylegan2/src/training/DiffAugment_tf.py c8f9bf34313b879d ran · fixture could not drive it fingerprinted licence not identified · pointer only
Analyzing and Improving the Image Quality of StyleGAN 3 Dec 2019 Di-Is/stylegan2-ada-pytorch/stylegan2_pytorch/diff_augment.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
Analyzing and Improving the Image Quality of StyleGAN 3 Dec 2019 lucidrains/stylegan2-pytorch/stylegan2_pytorch/diff_augment.py 31f2e654bb2eb0a1 unverified MIT (permissive)
arXiv:aaai_29065 UBCDingXin/Dual-NDA/SteeringAngle/SteeringAngle_128x128/CcGAN/NDA/DiffAugment_pytorch.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
arXiv:Ni_CHAIN_Enhancing_Generalization_in_Data-Efficient_GANs_via_lipsCHitz_continuity_constrAIned_CVPR_2024_paper MaxwellYaoNi/CHAIN/FastGANDBig/diffaug.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)
arXiv:136830137 hkust-vgd/neural_scene_decoration/lightweight_gan/diff_augment.py 5b0d8787e670fc63 ran · our draft was wrong fingerprinted MIT (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

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