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solarize

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

solarize appears in the code Syntology harvested for 15 papers, as 17 distinct code bodies found in 19 places (a place is one code body under one paper). At least one of them ran in 8 of the papers; 0 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 solarize 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 11 of the 17 distinct code bodies named solarize; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
8ran · our draft was wrong
1ran · fixture could not drive it
2ran
6unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 19 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

15 papers shown of 15, newest first; 19 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. 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
LDReg: Local Dimensionality Regularized Self-Supervised Learning 19 Jan 2024 JoJoNing25/DDAug/losses/ntxent_lidaug.py 8000f04f9e183df4 unverified MIT (permissive)
Learning to (Learn at Test Time) 20 Oct 2023 test-time-training/mttt/pp/autoaugment.py 2f023d4690a70195 ran Apache-2.0 (permissive)
MEMO: Test Time Robustness via Adaptation and Augmentation 18 Oct 2021 kowshikthopalli/sista/SISTA_DA/image_target_memo.py 7d16ac5dad904d6e ran · our draft was wrong no licence file found · pointer only
Learning Optimal Conformal Classifiers 18 Oct 2021 deepmind/conformal_training/auto_augment.py f483cc864d3d3300 unverified Apache-2.0 (permissive)
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain 19 Aug 2021 iCGY96/APR/datasets/APR.py 62f59af34932ce5f ran · our draft was wrong MIT (permissive)
FitVid: Overfitting in Pixel-Level Video Prediction 24 Jun 2021 google-research/fitvid/randaug.py 6a5f91515bf55921 unverified Apache-2.0 (permissive)
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples 28 Apr 2021 sayakpaul/PAWS-TF/utils/multicrop_loader.py 879172744bfa9ab1 unverified Apache-2.0 (permissive)
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration 2 Apr 2021 theot1/dign/DiGN.py 58bdedec5152aaaa ran · our draft was wrong MIT (permissive)
MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption 30 Mar 2021 AlexanderBartler/MT3/model/augementations/auto_augment.py e40dd3a18c0fb8bc unverified MIT (permissive)
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization 29 Jun 2020 hendrycks/imagenet-r/deepfashion_remix/augmix.py ea3db097ab0c59d3 ran · our draft was wrong MIT (permissive)
Smooth Adversarial Training 25 Jun 2020 cihangxie/SmoothAdversarialTraining/EfficientNet/autoaugment.py 2f023d4690a70195 ran MIT (permissive)
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 google-research/augmix/augment_and_mix.py 78f075a3d806fae7 ran · our draft was wrong Apache-2.0 (permissive)
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 ma7555/Augz/augmix.py 0112fdb1956a37d5 ran · our draft was wrong no licence file found · pointer only
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 Kaushal28/Bengali-AI/src/dataset.py 433a8a57c5669f13 ran · our draft was wrong no licence file found · pointer only
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 etetteh/sota-data-augmentation-and-optimizers/augmentation/AugMix/AugMix.py 174b8d6cc1208268 ran · our draft was wrong MIT (permissive)
Self-training with Noisy Student improves ImageNet classification 11 Nov 2019 google-research/noisystudent/randaugment.py e40dd3a18c0fb8bc unverified Apache-2.0 (permissive)
RandAugment: Practical automated data augmentation with a reduced search space 30 Sep 2019 nachiket273/pytorch_resnet_rs/model/randaugment.py b8a2aca46dc33d3f ran · fixture could not drive it MIT (permissive)
RandAugment: Practical automated data augmentation with a reduced search space 30 Sep 2019 lyxxn0414/test-data-generation/auto_augment.py f5999a1ee8824e22 ran no licence file found · pointer only
Objects as Points 16 Apr 2019 xuannianz/keras-CenterNet/augmentor/color.py 8e2fdb3504fc1330 unverified Apache-2.0 (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".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections