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total_variation

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

total_variation appears in the code Syntology harvested for 14 papers, as 9 distinct code bodies found in 14 places (a place is one code body under one paper). At least one of them ran in 1 of the papers; 1 of the code bodies carries 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 total_variation 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 1 of the 9 distinct code bodies named total_variation; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 2 of the 14 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

14 papers shown of 14, newest first; 14 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
From Deceptive Outputs to Deceptive Mechanisms: A Causal Framework for Language-Model Deception Research added by Syntology 2026-09 (from id) yshk-mxim/deceptive-mechanism/replication_package/experiment1/analysis/src/deceit_analysis/metrics.py 5a236a9c5479d07f unverified MIT (permissive)
ARES: Scalable and Practical Gradient Inversion Attack in Federated Learning through Activation Recovery added by Syntology 2026-03 (from id) gaow0007/ATSPrivacy/inversefed/metrics.py 3d23162c75564e01 unverified MIT (permissive)
Topology meets Machine Learning: An Introduction using the Euler Characteristic Transform 23 Oct 2024 aidos-lab/ECT/ect_image.py 1c472c25567e467e unverified BSD-3-Clause (permissive)
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning 2024-04 (from id) tasi-lab/unlearning-inversion-attacks/recovery/metrics.py 3d23162c75564e01 unverified no licence file found · pointer only
Understanding Deep Gradient Leakage via Inversion Influence Functions 22 Sep 2023 illidanlab/inversion-influence-function/inversefed/metrics.py 3d23162c75564e01 unverified MIT (permissive)
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization 9 Aug 2023 ffhibnese/GIFD/inversefed/metrics.py 3d23162c75564e01 unverified MIT (permissive)
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning 31 May 2023 junyizhu-ai/surrogate_model_extension/sme/Adversary/adversary.py 751c3b578dca1309 ran · fixture could not drive it fingerprinted no licence file found · pointer only
Gradient-Leakage Resilient Federated Learning 2 Jul 2021 KaiyuanZh/censor/inversefed/metrics.py 3d23162c75564e01 unverified MIT (permissive)
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch 5 Oct 2019 manyids2/kornia/kornia/losses/total_variation.py ace65b30a9175199 unverified Apache-2.0 (permissive)
Towards Near-imperceptible Steganographic Text 15 Jul 2019 falcondai/lm-steganography/bucket.py 5c50495d583afb43 unverified MIT (permissive)
RISE: Randomized Input Sampling for Explanation of Black-box Models 19 Jun 2018 vlue-c/PyTorch-Explanations/torchvex/meaningful_perturbation/mask.py b0396293b38da996 unverified MIT (permissive)
arXiv:Zhang_Generative_Gradient_Inversion_via_Over-Parameterized_Networks_in_Federated_Learning_ICCV_2023_paper czhang024/CI-Net/utils/reconstructed.py 4131f97dcfa84ceb unverified MIT (permissive)
arXiv:Sun_Soteria_Provable_Defense_Against_Privacy_Leakage_in_Federated_Learning_From_CVPR_2021_paper jeremy313/Soteria/GS_attack/inversefed/metrics.py 3d23162c75564e01 unverified MIT (permissive)
arXiv:Gan_GaussianOcc_Fully_Self-supervised_and_Efficient_3D_Occupancy_Estimation_with_Gaussian_ICCV_2025_paper GANWANSHUI/GaussianOcc/networks/occupancy_decoder.py 9951c8a5bcd02850 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