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compute_alpha

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

compute_alpha appears in the code Syntology harvested for 26 papers, as 7 distinct code bodies found in 26 places (a place is one code body under one paper). At least one of them ran in 19 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 compute_alpha 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 2 of the 7 distinct code bodies named compute_alpha; 5 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
1ran
5unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 26 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

26 papers shown of 26, newest first; 26 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 3 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
Consistency Models for Fast MRI Reconstruction Using Regularization by Denoising added by Syntology 2026-08 (from id) MerveGulle/CM-RED/functions/cm_red_scheme.py 77ec24266bd8b887 unverified no licence file found · pointer only
Noise-Adaptive Diffusion Sampling for Inverse Problems Without Task-Specific Tuning added by Syntology 2026-04 (from id) NA-HMC/NA-HMC/main_sampling.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers added by Syntology 2026-01 (from id) FlowDPS-Inverse/FlowDPS/functions/svd_ddnm.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
PSC: Posterior Sampling-Based Compression 13 Jul 2024 noamelata/AdaSense/functions/denoising.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models 27 May 2024 identical code first harvested elsewhere 9215fb189fbfb9f4 ran · our draft was wrong licence of this copy not recorded
Deep Data Consistency: a Fast and Robust Diffusion Model-based Solver for Inverse Problems 17 May 2024 hanyu-chen373/deepdataconsistency/functions/svd_ddnm.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned Guidance 27 Dec 2023 tirer-lab/ddpg/functions/ddpg_scheme.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation 25 Dec 2023 wyky481l/mmcd/util/diffusion_util.py eb16345c96520506 ran no licence file found · pointer only
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference 17 Oct 2023 karrykkk/BayesDiff/ddpm_and_guided/ddimUQ_utils.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook 16 Oct 2023 wenhaomin/DiffSTG/algorithm/diffstg/model.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement 27 Jul 2023 taowangzj/lldiffusion/models/ddm.py 9215fb189fbfb9f4 ran · our draft was wrong no licence file found · pointer only
Low-Light Image Enhancement with Wavelet-based Diffusion Models 1 Jun 2023 JianghaiSCU/Diffusion-Low-Light/utils/sampling.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Unlimited-Size Diffusion Restoration 1 Mar 2023 wyhuai/ddnm/functions/svd_ddnm.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration 30 Jan 2023 sony/gibbsddrm/functions/denoising.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction 26 Nov 2022 BaratiLab/Diffusion-based-Fluid-Super-resolution/functions/denoising_step.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Person Image Synthesis via Denoising Diffusion Model 22 Nov 2022 ankanbhunia/PIDM/diffusion.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Diffusion-GAN: Training GANs with Diffusion 5 Jun 2022 jegzheng/truncated-diffusion-probabilistic-models/functions/denoising.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Robustness of Graph Neural Networks at Scale 26 Oct 2021 sigeisler/robustness_of_gnns_at_scale/rgnn_at_scale/attacks/nettack.py 3dfa8f8448457f20 unverified MIT (permissive)
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets 27 Sep 2021 yanlai00/bridge_data_imitation_learning/bridgedata/models/utils/gradient_reversal_layer.py 4541f3b638b810b1 unverified MIT (permissive)
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation 12 Jun 2021 identical code first harvested elsewhere 9215fb189fbfb9f4 ran · our draft was wrong licence of this copy not recorded
Improved Denoising Diffusion Probabilistic Models 18 Feb 2021 g4vrel/DDPM/sample.py 9215fb189fbfb9f4 ran · our draft was wrong MIT (permissive)
Graph Random Neural Network for Semi-Supervised Learning on Graphs 22 May 2020 junzhuang-code/lindt/src/baselines/nettack/nettack.py 3dfa8f8448457f20 unverified MIT (permissive)
Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection 5 Mar 2019 zhixinwang/frustum-convnet/datasets/provider_sample.py 8d0c2b6ba5dcbf2d unverified MIT (permissive)
Adversarial Attacks on Neural Networks for Graph Data 21 May 2018 danielzuegner/nettack/nettack/nettack.py 3dfa8f8448457f20 unverified MIT (permissive)
Deep Learning with Differential Privacy 1 Jul 2016 sunblaze-ucb/dpml-benchmark/algorithms/frank_wolfe.py d9a28ecc659a537a unverified MIT (permissive)
arXiv:ijcai2024_0157 ShinyGua/DPMs-with-Adam/utils/denoising.py 9215fb189fbfb9f4 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