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densenet201

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

densenet201 appears in the code Syntology harvested for 21 papers, as 16 distinct code bodies found in 23 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 densenet201 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 16 distinct code bodies named densenet201; 12 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
2ran · our draft was wrong
0ran · fixture could not drive it
2ran
12unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 23 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

21 papers shown of 21, newest first; 23 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; 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
4-bit Shampoo for Memory-Efficient Network Training 28 May 2024 sike-wang/low-bit-shampoo/models/densenet.py b70932e817d72f6c ran no licence file found · pointer only
VMamba: Visual State Space Model 18 Jan 2024 zs1314/microscopic-mamba/baseline_other/CNN/densenet.py fe873ee58a22c0f7 unverified Apache-2.0 (permissive)
ReWaRD: Retinal Waves for Pre-Training Artificial Neural Networks Mimicking Real Prenatal Development 28 Nov 2023 bennyca/reward/4_Visualization/nets/densenet.py 22f2be1e9aacd878 ran licence not identified · pointer only
Shift-tolerant Perceptual Similarity Metric 27 Jul 2022 abhijay9/shifttolerant-lpips/models_lpf/densenet.py 0c253f6eb67013b8 unverified BSD-2-Clause (permissive)
On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition 26 May 2022 KingJamesSong/DifferentiableSVD/src/network/densenet.py c26ebe510580f5fa unverified Apache-2.0 (permissive)
Deep Unlearning via Randomized Conditionally Independent Hessians 15 Apr 2022 vsingh-group/LCODEC-deep-unlearning/scrub/deep-person-reid-master/torchreid/models/densenet.py 372747120f68c12f unverified MIT (permissive)
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time 10 Mar 2022 shallowlearn/sportsreid/torchreid/models/densenet.py 372747120f68c12f unverified MIT (permissive)
Can Vision Transformers Learn without Natural Images? 24 Mar 2021 hirokatsukataoka16/FractalDB-Pretrained-ResNet-PyTorch/finetuning/densenet.py 22f2be1e9aacd878 ran MIT (permissive)
Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification 12 Oct 2020 RQuispeC/top-dropblock/torchreid/models/densenet.py 14ea88b72b8a45f3 unverified MIT (permissive)
Calibrating Deep Neural Networks using Focal Loss 21 Feb 2020 torrvision/focal_calibration/Net/densenet.py 82dd30049f4202d8 unverified MIT (permissive)
Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch 22 Oct 2019 KaiyangZhou/deep-person-reid/torchreid/models/densenet.py 372747120f68c12f unverified MIT (permissive)
Exploiting temporal consistency for real-time video depth estimation 10 Aug 2019 weihaox/ST-CLSTM/models/densenet.py fb44f7825bd55074 unverified MIT (permissive)
Omni-Scale Feature Learning for Person Re-Identification 2 May 2019 donnjonn/Masterproef/torchreid/models/densenet.py 14ea88b72b8a45f3 unverified MIT (permissive)
Switchable Whitening for Deep Representation Learning 22 Apr 2019 XingangPan/Switchable-Whitening/models/backbones/densenet.py 9a4ab984f0c89842 unverified MIT (permissive)
Iterative Normalization: Beyond Standardization towards Efficient Whitening 6 Apr 2019 huangleiBuaa/IterNorm-pytorch/ImageNet/models/densenet.py 4db46650afe56128 unverified BSD-2-Clause (permissive)
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware 2 Dec 2018 ZTao-z/ProxylessNAS/training/net224x224/densenet.py 795a05cd8c775b28 unverified Apache-2.0 (permissive)
Manifold Mixup: Better Representations by Interpolating Hidden States 13 Jun 2018 identical code first harvested elsewhere 0ca25406530d858d unverified licence of this copy not recorded
Resource Aware Person Re-identification across Multiple Resolutions 22 May 2018 mileyan/DARENet/models/dare_densenet.py 61384669f2b43c43 unverified MIT (permissive)
Densely Connected Convolutional Networks 25 Aug 2016 jiweibo/imagenet/models/densenet.py ed4f95207d5e697e ran · our draft was wrong MIT (permissive)
Densely Connected Convolutional Networks 25 Aug 2016 fengjiqiang/pretrainedmodel_pytorch/densenet.py cc30af9ad8ab8701 ran · our draft was wrong Apache-2.0 (permissive)
Densely Connected Convolutional Networks 25 Aug 2016 DaikiTanak/manifold_mixup/densenet_mixup.py 0ca25406530d858d unverified no licence file found · pointer only
arXiv:Zhao_PhD_Learning_Learning_With_Pompeiu-Hausdorff_Distances_for_Video-Based_Vehicle_Re-Identification_CVPR_2021_paper emdata-ailab/PhD-Learning/torchreid/models/densenet.py 372747120f68c12f unverified Apache-2.0 (permissive)
arXiv:Liu_The_Devil_Is_in_the_Margin_Margin-Based_Label_Smoothing_for_CVPR_2022_paper by-liu/MbLS/calibrate/net/densenet.py 82dd30049f4202d8 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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