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preprocess_features

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

preprocess_features appears in the code Syntology harvested for 20 papers, as 16 distinct code bodies found in 20 places (a place is one code body under one paper). At least one of them ran in 11 of the papers; 2 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 preprocess_features 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 8 of the 16 distinct code bodies named preprocess_features; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 9 of the 20 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

20 papers shown of 20, newest first; 20 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 1 papers added by Syntology; 1 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
Benchmark Evaluation of Federated Learning on Multi-organ Images added by Syntology 2026-07 (from id) yutian0315/MobenFL/utils.py 1c361483c7cc9e34 ran no licence file found · pointer only
Privacy Attacks on Image AutoRegressive Models 4 Feb 2025 sprintml/privacy_attacks_against_iars/analysis/di.py c7b9775c61cf0e0c ran · honoured contract fingerprinted no licence file found · pointer only
Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts 18 Oct 2024 mala-lab/UNPrompt/utils.py 2c7fd193a4fb9c0f ran MIT (permissive)
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning 25 Sep 2024 zxlearningdeep/InfoMGF/InfoMGF/data_process.py a7f2485790a1d1c4 ran · our draft was wrong fingerprinted no licence file found · pointer only
Balanced Multi-Relational Graph Clustering 23 Jul 2024 zxlearningdeep/bmgc/BMGC/utils/load_data.py 2c7fd193a4fb9c0f ran no licence file found · pointer only
Diffusion-based Negative Sampling on Graphs for Link Prediction 25 Mar 2024 ntkien1904/dmns/data_process.py 93516a1ce7a5079f ran no licence file found · pointer only
GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation 22 Mar 2024 phd-lanyu/gtc/code/self_tools/data_tools.py 2c7fd193a4fb9c0f ran no licence file found · pointer only
Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering 21 Dec 2023 XweiQ/BTGF/load_data.py 2c7fd193a4fb9c0f ran no licence file found · pointer only
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection 18 Oct 2023 campanulabells/prem-gad/modules/utils.py d5abf636a0f1c18b ran no licence file found · pointer only
Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-Smoothing 7 Aug 2023 guoji-fu/dignn/nodeclassification/data.py 923136b4a244566b ran MIT (permissive)
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation 15 Jul 2023 jz48/mixupexplainer/MixupExplainer/ExplanationEvaluation/datasets/utils.py cf006ab979886496 ran no licence file found · pointer only
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability 25 Apr 2023 SitaoLuan/When-Do-GNNs-Help/utils/util_funcs.py 658057a59a7acc1a unverified MIT (permissive)
Improving Deep Metric Learning by Divide and Conquer 9 Sep 2021 compvis/metric-learning-divide-and-conquer-improved/metriclearning/faissext.py 38ac9dc17918d04e unverified MIT (permissive)
Semantically Coherent Out-of-Distribution Detection 26 Aug 2021 Jingkang50/ICCV21_SCOOD/scood/trainers/udg_trainer.py 294d6d9211fbcb70 unverified MIT (permissive)
Identity-Guided Human Semantic Parsing for Person Re-Identification 27 Jul 2020 CASIA-IVA-Lab/ISP-reID/engine/clustering.py 53f8b1e59f08664a unverified Apache-2.0 (permissive)
Rethinking deep active learning: Using unlabeled data at model training 19 Nov 2019 osimeoni/RethinkingDeepActiveLearning/lib/pretraining.py f71bd22cd58c9889 unverified MIT (permissive)
Spectral Clustering with Graph Neural Networks for Graph Pooling 30 Jun 2019 FilippoMB/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling/utils/citation.py e0296fe1142b4a69 unverified MIT (permissive)
Deep Bayesian Optimization on Attributed Graphs 31 May 2019 csjtx1021/DGBO/DeepSurrogateModel.py a306fefc42eebe49 unverified MIT (permissive)
Deep High-Resolution Representation Learning for Human Pose Estimation 25 Feb 2019 Vill-Lab/2022-TIP-HCGA/engine/clustering.py 53f8b1e59f08664a unverified MIT (permissive)
arXiv:aaai_29668 yhzhu66/RNCGLN/utils/process.py 0197b5d5b7be9292 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".

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