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normalize_features

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

normalize_features appears in the code Syntology harvested for 20 papers, as 15 distinct code bodies found in 20 places (a place is one code body under one paper). At least one of them ran in 10 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 normalize_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 6 of the 15 distinct code bodies named normalize_features; 9 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
2ran
9unverified
2fingerprinted

Licence is a property of each copy, so it is counted per place: 6 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 2 papers added by Syntology; 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
Assessing Sample Quality in Conditional Generation under Compositional Shift added by Syntology 2026-06 (from id) berkerdemirel/faithful-cond-gen/src/faithful_cond_gen/eval/trust_eval/scoring_core.py d668caea3552cf9c ran · our draft was wrong fingerprinted no licence file found · pointer only
SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From added by Syntology 2025-09 (from id) YnezT0311/SeedPrints/seedprint.py 4caeaca5a2027fa2 ran · fixture could not drive it no licence file found · pointer only
Training Robust Graph Neural Networks by Modeling Noise Dependencies 27 Feb 2025 WtaoZhao/GraphGLOW/src/core/model_handler.py 39cba20da9f36113 ran · our draft was wrong no licence file found · pointer only
Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis 4 Nov 2024 neel-dey/anatomix/anatomix/registration/registration_infrastructure/features.py ab04d4ab57907df5 unverified MIT (permissive)
TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features 22 Sep 2024 yandex-research/tabgraphs/source/ebbs/Base.py 2f4b2024843055fd ran MIT (permissive)
Towards Kinetic Manipulation of the Latent Space 15 Sep 2024 PDillis/stylegan3-fun/network_features.py 50b389807d1aa840 ran fingerprinted licence not identified · pointer only
GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation 22 Mar 2024 phd-lanyu/gtc/code/self_tools/adj_utils.py 39cba20da9f36113 ran · our draft was wrong no licence file found · pointer only
Multi-modal Contrastive Representation Learning for Entity Alignment 2 Sep 2022 lzxlin/mclea/src/utils.py 39cba20da9f36113 ran · our draft was wrong MIT (permissive)
Deformable Graph Convolutional Networks 29 Dec 2021 mlvlab/DeformableGCN/utils.py 39cba20da9f36113 ran · our draft was wrong MIT (permissive)
Reinforcement Learning with Dynamic Convex Risk Measures 26 Dec 2021 acoache/rl-dynamicconvexrisk/StatArbitrage/models.py 1e29d8be0861ded5 ran · our draft was wrong no licence file found · pointer only
Self-Supervised Multi-Frame Monocular Scene Flow 5 May 2021 visinf/multi-mono-sf/models/modules_sceneflow.py 9926e17e3fdfd75d unverified Apache-2.0 (permissive)
Visual Pivoting for (Unsupervised) Entity Alignment 28 Sep 2020 cambridgeltl/eva/src/utils.py 39cba20da9f36113 ran · our draft was wrong MIT (permissive)
What Matters in Unsupervised Optical Flow 8 Jun 2020 junbongjang/contour-tracking/src/contour_flow_model.py d0f7630cddfa3a3a unverified Apache-2.0 (permissive)
Relational Message Passing for Knowledge Graph Completion 17 Feb 2020 muhanzhang/IGMC/preprocessing.py 1e9e875e5b3efe21 unverified MIT (permissive)
Unifying Graph Convolutional Neural Networks and Label Propagation 17 Feb 2020 achalagarwal/gcn-lpa/src/data_loader.py 33746814a1d4ff92 unverified MIT (permissive)
The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction 17 Nov 2019 gauchm/ealstm_regional_modeling/papercode/datautils.py c37a05f06f05d465 unverified Apache-2.0 (permissive)
Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample Datasets 19 Jul 2019 kratzert/ealstm_regional_modeling/papercode/datautils.py c37a05f06f05d465 unverified Apache-2.0 (permissive)
Controlling the false discovery rate via knockoffs 2014-04 (from id) jrazi/KnockoffOrigins/knockofforigins/gram_matrix.py aef36a8aca14b59f unverified MIT (permissive)
arXiv:ijcai2023_0234 KellyGong/SparseGAD/utils.py c24e11d91a6e8f6a unverified MIT (permissive)
arXiv:aaai_25934 arghosh/DiFA/src/models/data_utils.py 7260787959e04dee 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".

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