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vgg11

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

vgg11 appears in the code Syntology harvested for 50 papers, as 43 distinct code bodies found in 51 places (a place is one code body under one paper). At least one of them ran in 15 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 11 of the 43 distinct code bodies named vgg11; 32 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
11ran
32unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 16 of the 51 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

50 papers shown of 50, newest first; 51 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; 6 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
Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks 25 Jun 2025 manyilee/plada/models/vgg.py 04cac479388fed8d unverified no licence file found · pointer only
On the Role of Label Noise in the Feature Learning Process 25 May 2025 zzp1012/label-noise-theory/src/model/cifar_vgg.py d1e094d5d233a629 unverified MIT (permissive)
DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity 30 Oct 2024 baekrok/DASH-Direction-Aware-SHrinking/models/VGG.py 60734baab4873655 unverified MIT (permissive)
SAMPa: Sharpness-aware Minimization Parallelized 14 Oct 2024 LIONS-EPFL/SAMPa/model/vgg.py d61c738bf16ec3c0 ran no licence file found · pointer only
Hybrid Mamba for Few-Shot Segmentation 29 Sep 2024 sam1224/hmnet/model/vgg.py 2067e75510fbe85e ran licence not identified · pointer only
Benchmarking the Attribution Quality of Vision Models 16 Jul 2024 visinf/idsds/models/vgg.py 76b1bf0c7e996f90 unverified Apache-2.0 (permissive)
Eliminating Feature Ambiguity for Few-Shot Segmentation 13 Jul 2024 sam1224/aenet/HDMNet/model/vgg.py 2067e75510fbe85e ran no licence file found · pointer only
4-bit Shampoo for Memory-Efficient Network Training 28 May 2024 sike-wang/low-bit-shampoo/models/vgg.py 05abe9f6c5347322 ran no licence file found · pointer only
Do Deep Neural Network Solutions Form a Star Domain? 12 Mar 2024 aktsonthalia/starlight/models/vgg.py 698439fe922fc6b0 ran MIT (permissive)
Learning with Logical Constraints but without Shortcut Satisfaction 1 Mar 2024 SoftWiser-group/NeSy-without-Shortcuts/models/vgg.py 7a6f63db4224099a unverified no licence file found · pointer only
NiteDR: Nighttime Image De-Raining with Cross-View Sensor Cooperative Learning for Dynamic Driving Scenes 28 Feb 2024 cidanshi/nitedr-nighttime-image-de-raining/vgg.py 5e2ed862866e2532 ran no licence file found · pointer only
VRP-SAM: SAM with Visual Reference Prompt 27 Feb 2024 syp2ysy/vrp-sam/model/base/vgg.py 2067e75510fbe85e ran MIT (permissive)
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model 1 Feb 2024 hzc1208/LMHT_SNN/ann_models/VGG.py a3ef124708d2a2b0 ran no licence file found · pointer only
Detection and Defense of Unlearnable Examples 14 Dec 2023 hala64/udp/model/VGG.py 0d8c3ebdac2fd8c9 ran no licence file found · pointer only
Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks 11 Dec 2023 yfguo91/ternary-spike/models/vggcifar.py 9c695d51a5fdcc9e unverified no licence file found · pointer only
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class Forgetting 1 Dec 2023 sangamesh-kodge/class_forgetting/models/vgg.py 89caa00e82add35d unverified no licence file found · pointer only
ReWaRD: Retinal Waves for Pre-Training Artificial Neural Networks Mimicking Real Prenatal Development 28 Nov 2023 bennyca/reward/4_Visualization/nets/vgg.py f92da55ca8690873 ran licence not identified · pointer only
On the Robustness of Neural Collapse and the Neural Collapse of Robustness 13 Nov 2023 jingtongsu/robust_neural_collapse/vgg_imagenet.py 26cf059b99797ae6 ran no licence file found · pointer only
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning 28 Oct 2023 guangyaodou/conmu/cv_models/VGG.py c766a8cd7888bd2d ran MIT (permissive)
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods 11 Aug 2023 visinf/funnybirds/funnybirds_complete/models/vgg.py 76b1bf0c7e996f90 unverified Apache-2.0 (permissive)
You Can Backdoor Personalized Federated Learning 29 Jul 2023 bapfl/code/models/Cifar10Net.py 9ef94bd9488b7ebe ran no licence file found · pointer only
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification 24 Jun 2023 xk-huang/OrdinalCLIP/ordinalclip/models/image_encoders/vgg.py 605fa285c125d097 unverified MIT (permissive)
Towards Universal Fake Image Detectors that Generalize Across Generative Models 20 Feb 2023 yuheng-li/universalfakedetect/models/vgg.py 04cac479388fed8d unverified MIT (permissive)
Not All Poisons are Created Equal: Robust Training against Data Poisoning 18 Oct 2022 yuyang0901/effective-poison-identification/models/vgg.py 57636423450ce2a4 unverified MIT (permissive)
Shift-tolerant Perceptual Similarity Metric 27 Jul 2022 abhijay9/shifttolerant-lpips/models_lpf/vgg.py 218e7087e99477df unverified BSD-2-Clause (permissive)
On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition 26 May 2022 KingJamesSong/DifferentiableSVD/src/network/vgg.py 9ec7dbb47bd1938b unverified Apache-2.0 (permissive)
Learning What Not to Segment: A New Perspective on Few-Shot Segmentation 15 Mar 2022 chunbolang/BAM/model/vgg.py 2067e75510fbe85e ran MIT (permissive)
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains 27 Jan 2022 Alibaba-AAIG/Beyond-ImageNet-Attack/imagenet/vgg.py 935d064cdc5a56c6 unverified MIT (permissive)
Phase Collapse in Neural Networks 11 Oct 2021 florentinguth/phasecollapse/models/vgg.py 7d04f93796ace37b unverified BSD-3-Clause (permissive)
Few-Shot Segmentation with Global and Local Contrastive Learning 11 Aug 2021 liuweide01/GQNet-Few-shot-segmentation/model/vgg.py 2067e75510fbe85e ran MIT (permissive)
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization 13 Jun 2021 conditionWang/NTL/src/ntl/ntl_digit.py 05433be5d7996335 unverified no licence file found · pointer only
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks 28 May 2021 DongyoungLim/THEO_POULA/models/vgg.py e4d45132558d0903 unverified MIT (permissive)
Learning Black-Box Attackers with Transferable Priors and Query Feedback 21 Oct 2020 TrustworthyDL/LeBA/imagenet/models/vgg.py 4e473b974953d3d3 unverified Apache-2.0 (permissive)
Regularizing Neural Networks via Adversarial Model Perturbation 10 Oct 2020 hiyouga/AMP-Regularizer/models/vgg.py c96e667a110ad914 unverified MIT (permissive)
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows 15 Jul 2020 hmdolatabadi/AdvFlow/vgg.py 9e8680c7bf44ac85 unverified MIT (permissive)
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks 22 Jun 2020 aks2203/poisoning-benchmark/models/vgg.py 57636423450ce2a4 unverified MIT (permissive)
Blind Backdoors in Deep Learning Models 8 May 2020 ebagdasa/backdoors101/models/vgg.py 1d6a9b32fa100d3a unverified MIT (permissive)
Disentangling Content and Style via Unsupervised Geometry Distillation 11 May 2019 pb2377/PyTorch-Disentangling-Content-and-Style-Unsupervised/vgg.py a97e757d44f4dc7f unverified MIT (permissive)
Iterative Normalization: Beyond Standardization towards Efficient Whitening 6 Apr 2019 huangleiBuaa/IterNorm-pytorch/ImageNet/models/vgg.py 3481975c041f9d95 unverified BSD-2-Clause (permissive)
Variational Adversarial Active Learning 31 Mar 2019 sinhasam/vaal/vgg.py c872dddd472f0138 unverified BSD-2-Clause (permissive)
Variational Adversarial Active Learning 31 Mar 2019 johntiger1/vaal_querying/vgg.py f6e25e358233c4bb unverified BSD-2-Clause (permissive)
Many Task Learning with Task Routing 28 Mar 2019 gstrezoski/TaskRouting/routed_vgg.py 40b0cc821f1fe2d5 unverified no licence file found · pointer only
Deep Learning under Privileged Information Using Heteroscedastic Dropout 29 May 2018 johnwlambert/dlupi-heteroscedastic-dropout/cnns/base_networks/vgg.py 9df6792345c6f27b unverified MIT (permissive)
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization 7 Oct 2016 tarolangner/mri-biometry/cnn/models/net_vgg.py 5d1eaa0429e5f67d unverified MIT (permissive)
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima 15 Sep 2016 keskarnitish/large-batch-training/PyTorch/vgg.py 42754302076e329d unverified MIT (permissive)
arXiv:aaai_33972 sangamesh-kodge/SAP/models/vgg.py 7806cd2294939410 unverified Apache-2.0 (permissive)
arXiv:aaai_28258 dongmo-qcq/FG-CAM/models/vgg.py 433690bc6124d57d unverified MIT (permissive)
arXiv:aaai_26027 UCAS-LCH/Twin-Rep/models/vgg.py e3fc0109a3a3c7ed unverified MIT (permissive)
arXiv:Pang_Backdoor_Cleansing_With_Unlabeled_Data_CVPR_2023_paper luluppang/BCU/models/vgg.py a97e757d44f4dc7f unverified MIT (permissive)
arXiv:136780474 dengyecode/hourglassattention/model/vgg.py 0f501772501ffd1e unverified MIT (permissive)
arXiv:03594 zouyuda220/SAE/models/vgg_.py 1a5e55f5b7603280 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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