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DenseNet121

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

DenseNet121 appears in the code Syntology harvested for 32 papers, as 20 distinct code bodies found in 34 places (a place is one code body under one paper). At least one of them ran in 22 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 DenseNet121 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 9 of the 20 distinct code bodies named DenseNet121; 11 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
8ran
11unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 34 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

32 papers shown of 32, newest first; 34 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 1 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
Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets? added by Syntology 2026-06 (from id) AyushRoy2001/ManifoldGD/train_models/densenet_cifar.py 19442a6a71144dbd ran no licence file found · pointer only
Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets? added by Syntology 2026-06 (from id) Jiacheng8/FADRM/models/densenet.py 3da7ee44118b27ad ran MIT (permissive)
FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation 30 Jun 2025 jiacheng8/fadrm/models/densenet.py 3da7ee44118b27ad ran MIT (permissive)
Dataset Distillation via Committee Voting 13 Jan 2025 jiacheng8/cv-dd/models/densenet.py 3da7ee44118b27ad ran MIT (permissive)
Dataset Distillers Are Good Label Denoisers In the Wild 18 Nov 2024 kciiiman/dd_lnl/DANCE+ours/models/densenet_cifar.py 19442a6a71144dbd ran no licence file found · pointer only
DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank Adaptation 16 Oct 2024 cuhk-aim-group/deer/models_dict/densenet.py 076b0d967ea9301b unverified no licence file found · pointer only
SAMPa: Sharpness-aware Minimization Parallelized 14 Oct 2024 LIONS-EPFL/SAMPa/model/densenet.py dfb395bae3d07d76 ran no licence file found · pointer only
A Method to Facilitate Membership Inference Attacks in Deep Learning Models 2 Jul 2024 DependableSystemsLab/code_poison_MIA/networks/densenet.py eddbdf4e2206ac0f ran MIT (permissive)
DANCE: Dual-View Distribution Alignment for Dataset Condensation 3 Jun 2024 Hansong-Zhang/DANCE/models/densenet_cifar.py 19442a6a71144dbd ran no licence file found · pointer only
Provably Unlearnable Data Examples 6 May 2024 neuralsec/certified-data-learnability/models/DenseNet.py dfb395bae3d07d76 ran no licence file found · pointer only
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders 2 May 2024 yuyi-sd/D-VAE/models/DenseNet.py dfb395bae3d07d76 ran MIT (permissive)
Multisize Dataset Condensation 10 Mar 2024 he-y/Multisize-Dataset-Condensation/models/densenet_cifar.py 19442a6a71144dbd ran MIT (permissive)
Optimizing Neural Networks with Gradient Lexicase Selection 19 Dec 2023 ld-ing/gradient-lexicase/models/densenet.py dfb395bae3d07d76 ran MIT (permissive)
You Only Condense Once: Two Rules for Pruning Condensed Datasets 21 Oct 2023 he-y/you-only-condense-once/models/densenet_cifar.py 19442a6a71144dbd ran no licence file found · pointer only
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees 21 Aug 2023 abductivelearning/abl-tl/models/densenet.py e88abd65e3c98af7 ran no licence file found · pointer only
APBench: A Unified Benchmark for Availability Poisoning Attacks and Defenses 7 Aug 2023 lafeat/apbench/nets/densenet.py 6cae1be82a92122d ran MIT (permissive)
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning 1 Aug 2023 Immortalise/RiFT/models/densenet.py 5b545f16f72c1645 ran no licence file found · pointer only
Locally Adaptive Federated Learning 12 Jul 2023 IssamLaradji/sps/src/base_classifiers.py ea1e46ba1761264d ran no licence file found · pointer only
LibAUC: A Deep Learning Library for X-Risk Optimization 5 Jun 2023 Optimization-AI/LibAUC/libauc/models/densenet.py 8a4d4b5c6865a4b2 unverified MIT (permissive)
UNICORN: A Unified Backdoor Trigger Inversion Framework 5 Apr 2023 ru-system-software-and-security/unicorn/models/densenet.py 4642fceedc1f27a6 unverified MIT (permissive)
The Devil's Advocate: Shattering the Illusion of Unexploitable Data using Diffusion Models 15 Mar 2023 hmdolatabadi/avatar/models/DenseNet.py a3cedf1d509b37f2 unverified MIT (permissive)
Target-based Surrogates for Stochastic Optimization 6 Feb 2023 wilderlavington/target-based-surrogates-for-stochastic-optimization/models.py 7a9e058c035f14cc unverified MIT (permissive)
Domain Adaptation under Open Set Label Shift 26 Jul 2022 acmi-lab/open-set-label-shift/models/Densenet.py 14e37cf982988836 unverified Apache-2.0 (permissive)
Dual Representation Learning for Out-of-Distribution Detection 19 Jun 2022 lawliet-zzl/drl/code/models/densenet.py dfb395bae3d07d76 ran MIT (permissive)
Can Adversarial Training Be Manipulated By Non-Robust Features? 31 Jan 2022 tlmichael/hypocritical-perturbation/models/densenet.py 580a043332af4a51 unverified MIT (permissive)
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators 23 Aug 2021 lawliet-zzl/fig/code_FIG/models/densenet.py dfb395bae3d07d76 ran MIT (permissive)
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks 28 May 2021 DongyoungLim/THEO_POULA/models/densenet.py dfb395bae3d07d76 ran MIT (permissive)
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration 2 Apr 2021 theot1/dign/DiGN.py e18432664d73b55f ran · our draft was wrong MIT (permissive)
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration 2 Apr 2021 TheoT1/DiGN/densenet.py 9ccdb4ad5a50fc5c unverified MIT (permissive)
Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia 29 Jun 2020 zeke-xie/adaptive-inertia-adai/model/densenet.py dfb395bae3d07d76 ran MIT (permissive)
Hold me tight! Influence of discriminative features on deep network boundaries 15 Feb 2020 LTS4/hold-me-tight/model_classes/cifar10/densenet.py 46d91f5224859d33 unverified Apache-2.0 (permissive)
Network Deconvolution 28 May 2019 deconvolutionpaper/deconvolution/models/densenet.py a848734514fda9d2 unverified Apache-2.0 (permissive)
arXiv:aaai_28784 Hansong-Zhang/M3D/models/densenet_cifar.py 19442a6a71144dbd ran MIT (permissive)
arXiv:aaai_28019 VinAIResearch/COMBAT/classifier_models/densenet.py 7ca32c7a6aa1ef41 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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