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gaussian_filter

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

gaussian_filter appears in the code Syntology harvested for 21 papers, as 14 distinct code bodies found in 22 places (a place is one code body under one paper). At least one of them ran in 9 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 gaussian_filter 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 5 of the 14 distinct code bodies named gaussian_filter; 9 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
1ran · fixture could not drive it
2ran
9unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 5 of the 22 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; 22 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; 3 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
MEIcoder: Decoding Visual Stimuli from Neural Activity by Leveraging Most Exciting Inputs added by Syntology 2025-10 (from id) Johnny1188/meicoder/csng/losses.py 28a8030dafe33601 unverified no licence file found · pointer only
Video Seal: Open and Efficient Video Watermarking 12 Dec 2024 facebookresearch/videoseal/videoseal/losses/ssim.py 4f04a1ea76a14dc9 unverified MIT (permissive)
AccDiffusion v2: Towards More Accurate Higher-Resolution Diffusion Extrapolation 3 Dec 2024 lzhxmu/accdiffusion_v2/accdiffusion_plus.py d62a181623d1f0cf ran · our draft was wrong no licence file found · pointer only
AP-LDM: Attentive and Progressive Latent Diffusion Model for Training-Free High-Resolution Image Generation 8 Oct 2024 kmittle/RepLDM/InferencePipelines/RepLDM/pipeline_repldm_sdxl.py d62a181623d1f0cf ran · our draft was wrong Apache-2.0 (permissive)
AP-LDM: Attentive and Progressive Latent Diffusion Model for Training-Free High-Resolution Image Generation 8 Oct 2024 kmittle/ap-ldm/InferencePipelines/FreeScale/scale_attention.py c4ce1939cbcf8432 ran Apache-2.0 (permissive)
PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation 8 Sep 2024 axi404/pmt/code/utils/ssim.py a45837742fe325cc ran no licence file found · pointer only
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Prompts 4 Sep 2024 Liuxinyv/HiPrompt/hiprompt_sdxl_llava.py d62a181623d1f0cf ran · our draft was wrong no licence file found · pointer only
AccDiffusion: An Accurate Method for Higher-Resolution Image Generation 15 Jul 2024 lzhxmu/AccDiffusion/accdiffusion_sdxl.py d62a181623d1f0cf ran · our draft was wrong no licence file found · pointer only
DemoFusion: Democratising High-Resolution Image Generation With No $$$ 24 Nov 2023 PRIS-CV/DemoFusion/pipeline_demofusion_sdxl_controlnet.py d62a181623d1f0cf ran · our draft was wrong MIT (permissive)
Few-Shot Domain Adaptation for Low Light RAW Image Enhancement 27 Mar 2023 Vishal-V/FSDA-LowLight/pytorch_msssim/ssim.py fd04084240f82190 unverified MIT (permissive)
Adversarial score matching and improved sampling for image generation 11 Sep 2020 AlexiaJM/AdversarialConsistentScoreMatching/losses/ssim.py ad0128e7c4e3e49b unverified MIT (permissive)
Comparison of Image Quality Models for Optimization of Image Processing Systems 4 May 2020 dingkeyan93/IQA-optimization/IQA_pytorch/SSIM.py e62294c5d41ce581 ran · fixture could not drive it MIT (permissive)
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules 6 Jan 2020 LiuLei95/PyTorch-Learned-Image-Compression-with-GMM-and-Attention/models/ms_ssim_torch.py 569f86999a28550f unverified Apache-2.0 (permissive)
Neural reparameterization improves structural optimization 10 Sep 2019 google-research/neural-structural-optimization/neural_structural_optimization/autograd_lib.py 84190a23c8eac7e1 unverified Apache-2.0 (permissive)
RISE: Randomized Input Sampling for Explanation of Black-box Models 19 Jun 2018 vlue-c/PyTorch-Explanations/torchvex/meaningful_perturbation/mask.py 049ca000aec357e1 unverified MIT (permissive)
ADef: an Iterative Algorithm to Construct Adversarial Deformations 20 Apr 2018 MashmallowWoR/AdversarialDeformation/deformation.py 553839a61a4e4927 ran · our draft was wrong Apache-2.0 (permissive)
End-to-end Optimized Image Compression 5 Nov 2016 liujiaheng/iclr_17_compression/models/ms_ssim_torch.py 569f86999a28550f unverified MIT (permissive)
Going Deeper with Convolutions 17 Sep 2014 HolmesShuan/AIM2020-RealSR/src/calculate_score.py 569f86999a28550f unverified BSD-2-Clause (permissive)
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks 20 Dec 2013 Factotum8/test_task_street_view_house_numbers/CNN_eval.py cb97dd4d6528d2bd unverified MIT (permissive)
arXiv:Yang_TINC_Tree-Structured_Implicit_Neural_Compression_CVPR_2023_paper RichealYoung/TINC/utils/ssim.py aff2d226c2edfa22 unverified MIT (permissive)
arXiv:Wang_MCF_Mutual_Correction_Framework_for_Semi-Supervised_Medical_Image_Segmentation_CVPR_2023_paper WYC-321/MCF/code/utils/ssim.py a45837742fe325cc ran MIT (permissive)
arXiv:Huang_Fast_Light-Field_Disparity_Estimation_With_Multi-Disparity-Scale_Cost_Aggregation_ICCV_2021_paper zcong17huang/FastLFnet/codeStep1/utils/loss_function.py 569f86999a28550f 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".

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