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epoch

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

epoch appears in the code Syntology harvested for 23 papers, as 19 distinct code bodies found in 24 places (a place is one code body under one paper). At least one of them ran in 4 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 epoch 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 4 of the 19 distinct code bodies named epoch; 15 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
0ran · fixture could not drive it
4ran
15unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 15 of the 24 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

23 papers shown of 23, newest first; 24 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
Dataset Distillation by Automatic Training Trajectories 19 Jul 2024 NiaLiu/ATT/utils_baseline.py cf303e03d7c1efe6 unverified no licence file found · pointer only
Convolutional Kolmogorov-Arnold Networks 19 Jun 2024 antoniotepsich/convolutional-kans/evaluations.py 995ad009fb73798e ran MIT (permissive)
A Label is Worth a Thousand Images in Dataset Distillation 15 Jun 2024 sunnytqin/no-distillation/softlabel/utils.py d9e7ac158739d955 unverified no licence file found · pointer only
Low-Rank Similarity Mining for Multimodal Dataset Distillation 6 Jun 2024 silicx/LoRS_Distill/src/epoch.py 7d65df8b482e868e ran BSD-3-Clause (permissive)
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching 28 May 2024 Yongalls/SelMatch/distill.py 32fbd0b361e6d136 unverified no licence file found · pointer only
Subhomogeneous Deep Equilibrium Models 1 Mar 2024 COMPiLELab/SubDEQ/utils.py c1a0e425aad156f4 ran no licence file found · pointer only
Dataset Distillation via Adversarial Prediction Matching 14 Dec 2023 mchen725/DD_APM/model_train/utils_train.py 64d02f5d7bdb507e unverified no licence file found · pointer only
Dataset Distillation via Adversarial Prediction Matching 14 Dec 2023 mchen725/DD_APM/utils.py 5bc5731862f0ff1c unverified no licence file found · pointer only
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm 6 Dec 2023 shaoshitong/EDC/Branch_CIFAR_10/recover/baseline.py cf303e03d7c1efe6 unverified no licence file found · pointer only
Discovering Galaxy Features via Dataset Distillation 29 Nov 2023 HaowenGuan/Galaxy-Dataset-Distillation/utils.py 50bd7c09c0d438af unverified licence not identified · pointer only
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching 29 Nov 2023 identical code first harvested elsewhere cf303e03d7c1efe6 unverified licence of this copy not recorded
DataDAM: Efficient Dataset Distillation with Attention Matching 29 Sep 2023 datadistillation/datadam/main_DataDAM.py d420983fabce48c3 unverified no licence file found · pointer only
Circuit Breaking: Removing Model Behaviors with Targeted Ablation 12 Sep 2023 xanderdavies/circuit-breaking/mnist/train_eval.py 5cefb8a41654c608 unverified no licence file found · pointer only
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power 10 Sep 2023 zml72062/dr-fwl-2/ogbmol_models.py e8d7a3ce2782fd96 ran no licence file found · pointer only
Improved Distribution Matching for Dataset Condensation 19 Jul 2023 uitrbn/idm/utils.py cf303e03d7c1efe6 unverified no licence file found · pointer only
Bayesian Pseudo-Coresets via Contrastive Divergence 20 Mar 2023 backpropagator/bpc-cd/utils.py cf303e03d7c1efe6 unverified MIT (permissive)
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations 2 Feb 2023 a514514772/fedlap-dp/utils/ops.py 68185a4f54101d97 unverified MIT (permissive)
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory 19 Nov 2022 justincui03/tesla/utils.py 595133eb1d0d162d unverified MIT (permissive)
Private Set Generation with Discriminative Information 7 Nov 2022 DingfanChen/Private-Set/utils/ops.py 68185a4f54101d97 unverified MIT (permissive)
Dataset Distillation via Factorization 30 Oct 2022 huage001/datasetfactorization/utils.py ab493433d379032e unverified Apache-2.0 (permissive)
CAFE: Learning to Condense Dataset by Aligning Features 3 Mar 2022 kaiwang960112/cafe/distill.py 6fa52b79ca3583aa unverified no licence file found · pointer only
Formalizing and Estimating Distribution Inference Risks 13 Sep 2021 iamgroot42/form_est_dist_risks/botnets/model_utils.py af78cce3251607a4 unverified BSD-2-Clause (permissive)
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks 12 Nov 2019 zero-or-one/URP/learning/learn.py f8191305d90db998 unverified MIT (permissive)
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models 3 Jun 2019 pawelmorawiecki/Fast-and-stable-IBP/IBP_SVHN_medium-1.py 0a3bead9a6d56105 unverified no licence file found · pointer only

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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