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to_categorical

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

to_categorical appears in the code Syntology harvested for 25 papers, as 18 distinct code bodies found in 25 places (a place is one code body under one paper). At least one of them ran in 11 of the papers; 3 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 to_categorical 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 7 of the 18 distinct code bodies named to_categorical; 11 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
3ran · our draft was wrong
1ran · fixture could not drive it
3ran
11unverified
3fingerprinted

Licence is a property of each copy, so it is counted per place: 8 of the 25 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

25 papers shown of 25, newest first; 25 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; 2 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
Trap-MID: Trapdoor-based Defense against Model Inversion Attacks 13 Nov 2024 ntuaislab/trap-mid/loss.py af8945c5f03a178f ran · our draft was wrong MIT (permissive)
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning 26 Aug 2024 tangw-seu/elimipl/dataloader.py 4e933e0cee3df94d ran no licence file found · pointer only
Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping 6 Feb 2024 cleverhans-lab/cleverhans/cleverhans/utils.py de49d6cc85bc9295 ran MIT (permissive)
Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated Learning 29 Nov 2023 ellisalicante/ma-fl-mia/trajectoryMIA.py 1bfe4f56727f2aba ran · our draft was wrong fingerprinted no licence file found · pointer only
3DCoMPaT$^{++}$: An improved Large-scale 3D Vision Dataset for Compositional Recognition 27 Oct 2023 cattalyya/3dcompat-challenge/models/3D/compat_utils.py 66a55d4a270861e8 ran fingerprinted BSD-3-Clause (permissive)
An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data 18 Aug 2022 identical code first harvested elsewhere 767b99615bbda28e ran · our draft was wrong fingerprinted licence of this copy not recorded
Increasing the accuracy and resolution of precipitation forecasts using deep generative models 23 Mar 2022 raspstephan/nwp-downscale/src/utils.py 756e409ad0425379 unverified MIT (permissive)
3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient 10 Jan 2022 ibm/multimodal-3d-image-segmentation/experiments/utils.py c448fb68d0f2e025 unverified Apache-2.0 (permissive)
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning 8 Jun 2021 microsoft/Playvirtual/DMControl/src/cycdm_sac.py 58d78f74ec58f2fc unverified MIT (permissive)
PCT: Point cloud transformer 17 Dec 2020 qq456cvb/Point-Transformers/train_partseg.py 767b99615bbda28e ran · our draft was wrong fingerprinted MIT (permissive)
Point Transformer 2 Nov 2020 identical code first harvested elsewhere 767b99615bbda28e ran · our draft was wrong fingerprinted licence of this copy not recorded
Improving Calibration through the Relationship with Adversarial Robustness 29 Jun 2020 tensorflow/cleverhans/cleverhans/utils.py de49d6cc85bc9295 ran MIT (permissive)
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks 21 Apr 2020 sancharisen/EMPIR/cleverhans/utils.py 436b1ff1875d0cc7 unverified MIT recorded; this copy not marked cleared · pointer only
MixMatch: A Holistic Approach to Semi-Supervised Learning 6 May 2019 gan3sh500/mixmatch-pytorch/mixmatch_utils.py 7ccbcdef1f97bdbf ran · fixture could not drive it no licence file found · pointer only
PointConv: Deep Convolutional Networks on 3D Point Clouds 17 Nov 2018 DylanWusee/pointconv_pytorch/utils/utils.py 767b99615bbda28e ran · our draft was wrong fingerprinted MIT (permissive)
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models 4 Jun 2018 arafin-lab/model_inversion_experiments/Utils/datasets.py aa760f81e898ab53 unverified Apache-2.0 (permissive)
Attacking Binarized Neural Networks 1 Nov 2017 AngusG/cleverhans-attacking-bnns/cleverhans/utils.py 436b1ff1875d0cc7 unverified MIT recorded; this copy not marked cleared · pointer only
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks 7 Oct 2016 hendrycks/error-detection/Vision/load_cifar10.py 70f5b5175a23f59d unverified MIT (permissive)
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library 3 Oct 2016 HowToMakeABomb101/Hot2MakeAB0mbSite/cleverhans/utils.py 6a9d90c5e5abd370 unverified MIT recorded; this copy not marked cleared · pointer only
Early Methods for Detecting Adversarial Images 1 Aug 2016 hendrycks/fooling/CIFAR/load_cifar10.py 70f5b5175a23f59d unverified MIT (permissive)
Gaussian Error Linear Units (GELUs) 27 Jun 2016 hendrycks/GELUs/load_cifar10.py 70f5b5175a23f59d unverified MIT (permissive)
Deep Recurrent Neural Networks for Supernovae Classification 23 Jun 2016 adammoss/supernovae/dataset.py e3225138fbcdb30a unverified MIT (permissive)
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets 12 Jun 2016 eriklindernoren/PyTorch-GAN/implementations/infogan/infogan.py 0d666ee36db81e43 unverified MIT (permissive)
arXiv:ijcai2021_0350 fudonglin/IMSIC/source/utils.py ce87b25b8a37143f unverified MIT (permissive)
arXiv:aaai_28047 ksandeshk/LENS/Flower/data_utils.py ca9076577f084d46 unverified 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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