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VGG11

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

VGG11 appears in the code Syntology harvested for 36 papers, as 19 distinct code bodies found in 42 places (a place is one code body under one paper). At least one of them ran in 17 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 VGG11 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 12 of the 19 distinct code bodies named VGG11; 7 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
4ran · our draft was wrong
0ran · fixture could not drive it
8ran
7unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 27 of the 42 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

36 papers shown of 36, newest first; 42 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; 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
Fair Dataset Distillation via Cross-Group Barycenter Alignment added by Syntology 2026-05 (from id) mhmoslemi/COBRA/networks.py 3a29eb3050e447c2 ran MIT (permissive)
Fair Dataset Distillation via Cross-Group Barycenter Alignment added by Syntology 2026-05 (from id) mhmoslemi/COBRA/cafe/networks.py f8401a9b3126d921 ran MIT (permissive)
Rethinking Dataset Distillation: Hard Truths About Soft Labels added by Syntology 20 Apr 2026 NUS-HPC-AI-Lab/DATM/networks.py 2e6f03f47dc4131d unverified no licence file found · pointer only
Going Beyond Feature Similarity: Effective Dataset Distillation based on Class-Aware Conditional Mutual Information 13 Dec 2024 ndhg1213/CMIDD/DC-DSA-DM/networks.py 8e1b179ef1f0fe03 unverified no licence file found · pointer only
Dataset Distillers Are Good Label Denoisers In the Wild 18 Nov 2024 kciiiman/dd_lnl/DATM+ours/networks.py 2e6f03f47dc4131d unverified no licence file found · pointer only
Dataset Distillers Are Good Label Denoisers In the Wild 18 Nov 2024 kciiiman/dd_lnl/RCIG+ours/models.py 705d6efdfd6176e7 unverified no licence file found · pointer only
Color-Oriented Redundancy Reduction in Dataset Distillation 18 Nov 2024 KeViNYuAn0314/AutoPalette/networks.py 2e6f03f47dc4131d unverified no licence file found · pointer only
Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios 22 Oct 2024 nus-hpc-ai-lab/edf/networks.py 2e6f03f47dc4131d unverified no licence file found · pointer only
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks 3 Oct 2024 BigML-CS-UCLA/MKDT/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Dataset Distillation by Automatic Training Trajectories 19 Jul 2024 NiaLiu/ATT/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Low-Rank Similarity Mining for Multimodal Dataset Distillation 6 Jun 2024 silicx/LoRS_Distill/src/networks.py 190dfb67aacf4767 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 699b6b81e84201eb ran · our draft was wrong no licence file found · pointer only
Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation 31 Mar 2024 VincenDen/IID/IDM+ours/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation 31 Mar 2024 VincenDen/IID/IDM+ours/dc_networks.py ec3c9224d4a0353f ran no licence file found · pointer only
Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation 31 Mar 2024 VincenDen/IID/DM+ours/networks.py 8e1b179ef1f0fe03 unverified no licence file found · pointer only
Dataset Condensation for Time Series Classification via Dual Domain Matching 12 Mar 2024 zhyliu00/TimeSeriesCond/model/TSmodels.py dd623123fc74df82 ran no licence file found · pointer only
Distributional Dataset Distillation with Subtask Decomposition 1 Mar 2024 sunnytqin/d3/networks.py 369e271a765fa529 ran licence not identified · pointer only
Improve Cross-Architecture Generalization on Dataset Distillation 20 Feb 2024 distill-generalization-group/distill-generalization/src/networks.py 8e1b179ef1f0fe03 unverified no licence file found · pointer only
Dataset Distillation via Adversarial Prediction Matching 14 Dec 2023 mchen725/DD_APM/model_train/networks_train.py 190dfb67aacf4767 ran no licence file found · pointer only
Dataset Distillation via Adversarial Prediction Matching 14 Dec 2023 mchen725/DD_APM/networks.py 2a656ce9d92fa5c9 ran no licence file found · pointer only
Discovering Galaxy Features via Dataset Distillation 29 Nov 2023 HaowenGuan/Galaxy-Dataset-Distillation/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching 29 Nov 2023 shaoshitong/G_VBSM_Dataset_Condensation/Branch_CIFAR_10/recover/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Frequency Domain-based Dataset Distillation 15 Nov 2023 sdh0818/FreD/DC/networks.py 8e1b179ef1f0fe03 unverified Apache-2.0 (permissive)
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching 9 Oct 2023 nus-hpc-ai-lab/datm/networks.py 2e6f03f47dc4131d unverified no licence file found · pointer only
Can pre-trained models assist in dataset distillation? 5 Oct 2023 yaolu-zjut/ddinterpreter/utils_clom/model.py 8e1b179ef1f0fe03 unverified no licence file found · pointer only
DataDAM: Efficient Dataset Distillation with Attention Matching 29 Sep 2023 datadistillation/datadam/main_DataDAM.py d0f0d585cc626bd7 ran · our draft was wrong no licence file found · pointer only
Improved Distribution Matching for Dataset Condensation 19 Jul 2023 uitrbn/idm/networks.py 190dfb67aacf4767 ran no licence file found · pointer only
Improved Distribution Matching for Dataset Condensation 19 Jul 2023 uitrbn/idm/dc_networks.py 8e1b179ef1f0fe03 unverified no licence file found · pointer only
Fair yet Asymptotically Equal Collaborative Learning 9 Jun 2023 xqlin98/Fair-yet-Equal-CML/utils/models_defined.py 7a48517be70a2b3a unverified MIT (permissive)
Distill Gold from Massive Ores: Bi-level Data Pruning towards Efficient Dataset Distillation 28 May 2023 silicx/goldfromores/DatasetCondensation/networks.py 8e1b179ef1f0fe03 unverified MIT (permissive)
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations 2 Feb 2023 a514514772/fedlap-dp/utils/networks.py 8e1b179ef1f0fe03 unverified MIT (permissive)
Backdoor Attacks Against Dataset Distillation 3 Jan 2023 liuyugeng/baadd/DC/networks.py 190dfb67aacf4767 ran Apache-2.0 (permissive)
Private Set Generation with Discriminative Information 7 Nov 2022 DingfanChen/Private-Set/utils/networks.py 8e1b179ef1f0fe03 unverified MIT (permissive)
Dataset Distillation via Factorization 30 Oct 2022 huage001/datasetfactorization/networks.py 3add7fc8542fbd6b unverified Apache-2.0 (permissive)
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks 24 May 2022 cychomatica/one-pixel-shotcut/model/VGG.py e4759822cc516831 unverified Apache-2.0 (permissive)
Synthesizing Informative Training Samples with GAN 15 Apr 2022 VICO-UoE/DatasetCondensation/networks.py 8e1b179ef1f0fe03 unverified MIT (permissive)
CAFE: Learning to Condense Dataset by Aligning Features 3 Mar 2022 kaiwang960112/cafe/distill.py 955fe26af93adacd ran · our draft was wrong no licence file found · pointer only
Federated Learning Based on Dynamic Regularization 8 Nov 2021 thejungwon/gc-fed/algorithms/gcfed.py f0aeb868a782b3d7 ran · metamorphic tier: deterministic no licence file found · pointer only
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-Time 22 Feb 2019 gabrielhuang/centroid-networks/protonets/models/vgg.py 14e45238d8020ce8 unverified MIT (permissive)
Multi-class Classification without Multi-class Labels 2 Jan 2019 GT-RIPL/L2C/models/vgg.py 14e45238d8020ce8 unverified MIT (permissive)
Very Deep Convolutional Networks for Large-Scale Image Recognition 4 Sep 2014 CryptoSalamander/pytorch_paper_implementation/vgg/vgg.py d8c07e278a45ed42 ran · our draft was wrong no licence file found · pointer only
arXiv:03030 silicx/GoldFromOres-BiLP/DatasetCondensation/networks.py 8e1b179ef1f0fe03 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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