Home › Code › lr_scheduler

lr_scheduler

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

lr_scheduler appears in the code Syntology harvested for 32 papers, as 18 distinct code bodies found in 34 places (a place is one code body under one paper). At least one of them ran in 26 of the papers; 2 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 lr_scheduler 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 18 distinct code bodies named lr_scheduler; 7 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

4ran · honoured contract
0ran · violated contract
5ran · our draft was wrong
0ran · fixture could not drive it
2ran
7unverified
2fingerprinted

Licence is a property of each copy, so it is counted per place: 19 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
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation added by Syntology 2026-07 (from id) identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context 18 Dec 2024 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework 19 Nov 2024 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
LEAD: Learning Decomposition for Source-free Universal Domain Adaptation 6 Mar 2024 ispc-lab/glc/train_source.py 0b7ffc9f8b77529c ran · our draft was wrong no licence file found · pointer only
Contrastive Transformer Learning with Proximity Data Generation for Text-Based Person Search 15 Nov 2023 hcplab-sysu/personsearch-ctlg/function.py 87e153290f393327 ran no licence file found · pointer only
Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification 6 Jul 2023 yuyongcan/benchmark-tta/train_source.py 0b7ffc9f8b77529c ran · our draft was wrong no licence file found · pointer only
PLIP: Language-Image Pre-training for Person Representation Learning 15 May 2023 zplusdragon/plip/utils.py a31fc96a7b978b35 unverified MIT (permissive)
Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning 12 Nov 2022 zyezhang/dac/VisDA/target.py b7e334f5e0eb5920 ran · our draft was wrong GPL-3.0 (copyleft) · pointer only
Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention 11 Nov 2022 monstersecond/dasbe/dasbe/train_clrnet.py acc54adbeafc8bec unverified MIT (permissive)
Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention 11 Nov 2022 monstersecond/dasbe/dasbe/train_net.py 02df8fd7598f2c2b unverified MIT (permissive)
CoNMix for Source-free Single and Multi-target Domain Adaptation 7 Nov 2022 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
Uncertainty-Induced Transferability Representation for Source-Free Unsupervised Domain Adaptation 30 Aug 2022 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation 27 Jul 2022 albert0147/sfda_neighbors/train_src.py 0b7ffc9f8b77529c ran · our draft was wrong MIT (permissive)
Prior Knowledge Guided Unsupervised Domain Adaptation 18 Jul 2022 tsun/KUDA/DINE/DINE_dist.py 0b7ffc9f8b77529c ran · our draft was wrong MIT (permissive)
Confidence Score for Source-Free Unsupervised Domain Adaptation 14 Jun 2022 jhyun17/cowa-jmds/image_target_CoWA.py 1ee7b6c67ccbf3fb ran MIT (permissive)
ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation 29 May 2022 identical code first harvested elsewhere f46ea90b31f5948a ran · our draft was wrong licence of this copy not recorded
MM-BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic 13 May 2022 wanghangpsu/mm-bd/univ_bd.py a97f204f592690b1 ran · honoured contract fingerprinted no licence file found · pointer only
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation 9 May 2022 albert0147/aad_sfda/tar_adaptation.py 0b7ffc9f8b77529c ran · our draft was wrong no licence file found · pointer only
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation 1 Feb 2022 maohaos2/MSFDA/train_source.py 0b7ffc9f8b77529c ran · our draft was wrong MIT (permissive)
Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation 27 Jul 2021 tntek/N2DCX/object/N2DCEX_target.py 0b7ffc9f8b77529c ran · our draft was wrong MIT (permissive)
Randomness In Neural Network Training: Characterizing The Impact of Tooling 22 Jun 2021 usyd-fsalab/NeuralNetworkRandomness/src/training_script/resnet_celeba.py 384218efc7e9fdd8 unverified MIT (permissive)
DINE: Domain Adaptation from Single and Multiple Black-box Predictors 4 Apr 2021 tim-learn/Dis-tune/DINE_dist.py 0b7ffc9f8b77529c ran · our draft was wrong MIT (permissive)
DINE: Domain Adaptation from Single and Multiple Black-box Predictors 4 Apr 2021 tim-learn/dine/DINE_ft.py 8bd136d4257e40ea ran · our draft was wrong MIT (permissive)
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer 14 Dec 2020 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
Domain Adaptation with Auxiliary Target Domain-Oriented Classifier 8 Jul 2020 tim-learn/atdoc/demo_uda.py f46ea90b31f5948a ran · our draft was wrong MIT (permissive)
Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences 2 May 2020 hewh16/SNNs-RNNs/N-MNIST/nmnist_snn.py ccc54468ebc4ee84 ran · our draft was wrong no licence file found · pointer only
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation 20 Feb 2020 identical code first harvested elsewhere 0b7ffc9f8b77529c ran · our draft was wrong licence of this copy not recorded
Distance-Based Regularisation of Deep Networks for Fine-Tuning 19 Feb 2020 henrygouk/mars-finetuning/finetune.py aab819df6ce20af6 unverified no licence file found · pointer only
Learned Step Size Quantization 21 Feb 2019 zhutmost/lsq-net/util/lr_scheduler.py 39de768061885cd0 unverified MIT (permissive)
Decoupled Greedy Learning of CNNs 23 Jan 2019 eugenium/DGL/dni_comparisons/cifar_cnn_dni.py f81566b35c748e30 ran · honoured contract no licence file found · pointer only
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices 20 Apr 2018 godofpdog/MobileFaceNet_keras/src/build_model.py 64d058db63223637 ran · honoured contract fingerprinted no licence file found · pointer only
Pixel Recursive Super Resolution 2 Feb 2017 abhran/Pixel-Recursive-Super-resolution/model.py 9ed1db0f8b2c5a7b ran · honoured contract no licence file found · pointer only
arXiv:Ozdenizci_Improving_Robustness_Against_Stealthy_Weight_Bit-Flip_Attacks_by_Output_Code_CVPR_2022_paper IGITUGraz/OutputCodeMatching/utils/schedules.py 6bcbaa367995adaf unverified MIT (permissive)
arXiv:Liang_DINE_Domain_Adaptation_From_Single_and_Multiple_Black-Box_Predictors_CVPR_2022_paper tim-learn/DINE/DINE_dist.py 0b7ffc9f8b77529c ran · our draft was wrong 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".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections