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gaussian_nll

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

gaussian_nll appears in the code Syntology harvested for 8 papers, as 9 distinct code bodies found in 9 places (a place is one code body under one paper). At least one of them ran in 5 of the papers; 5 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_nll 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 6 of the 9 distinct code bodies named gaussian_nll; 3 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
0ran · violated contract
3ran · our draft was wrong
0ran · fixture could not drive it
2ran
3unverified
5fingerprinted

Licence is a property of each copy, so it is counted per place: 5 of the 9 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

8 papers shown of 8, newest first; 9 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. 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
Transformed Latent Variable Multi-Output Gaussian Processes added by Syntology 2026-05 (from id) XiaoyuJiang17/T-LVMOGP-official/models/dkl_lvmogp_base.py 0e305ed959c99458 ran · our draft was wrong fingerprinted MIT (permissive)
Multi Time Scale World Models 27 Oct 2023 ALRhub/MTS3/utils/Losses.py 67dea81cea22a2b4 ran fingerprinted no licence file found · pointer only
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction 31 Jul 2023 yvonneywu/udama/utils.py 5c4f3b3c8c96ff39 ran no licence file found · pointer only
Weakly Supervised Disentangled Generative Causal Representation Learning 6 Oct 2020 xwshen51/DEAR/bgm.py 5f841bea5a7712f0 unverified Apache-2.0 (permissive)
Pseudo-Rehearsal for Continual Learning with Normalizing Flows 5 Jul 2020 ispamm/PRER/continual_ai/cl_strategies/multi_task/prer/PRER.py 4eaf1511053dc8a7 ran · our draft was wrong fingerprinted no licence file found · pointer only
Simple and Effective VAE Training with Calibrated Decoders 23 Jun 2020 orybkin/sigma-vae-pytorch/model.py 85038890e349231c ran · our draft was wrong fingerprinted no licence file found · pointer only
Simple and Effective VAE Training with Calibrated Decoders 23 Jun 2020 orybkin/sigma-vae-pytorch/model.py b67c41c224081421 ran · honoured contract fingerprinted no licence file found · pointer only
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning 3 Jan 2020 soochan-lee/CN-DPM/loss.py 2a49059cf0583654 unverified MIT (permissive)
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning 29 Oct 2018 arnab39/FewShot_GAN-Unet3D/tensorflow/lib/operations.py 96330c807f450c14 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