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mean_absolute_percentage_error

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

mean_absolute_percentage_error appears in the code Syntology harvested for 10 papers, as 8 distinct code bodies found in 11 places (a place is one code body under one paper). At least one of them ran in 3 of the papers; 3 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 mean_absolute_percentage_error 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 3 of the 8 distinct code bodies named mean_absolute_percentage_error; 5 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 4 of the 11 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

10 papers shown of 10, newest first; 11 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 2 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
Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations added by Syntology 2026-08 (from id) pigofmomo/CLPINN/deepxde/losses.py 642a817822586843 unverified no licence file found · pointer only
A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations added by Syntology 2026-02 (from id) YerevaNN/mimic3-benchmarks/mimic3models/metrics.py bf861a65a6b445b6 unverified MIT (permissive)
Numerical Schemes for Signature Kernels 12 Feb 2025 francescopiatti/polysigkernel/experiments/error_analysis.py cb11a62f2210930e ran · violated contract fingerprinted Apache-2.0 (permissive)
PINNACLE: PINN Adaptive ColLocation and Experimental points selection 11 Apr 2024 apivich-h/pinnacle/pinnacle_code/deepxde_al_patch/deepxde/losses.py 642a817822586843 unverified no licence file found · pointer only
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs 15 Jun 2023 i207m/pinnacle/deepxde/losses.py 642a817822586843 unverified MIT (permissive)
Unified Spatio-Temporal Modeling for Traffic Forecasting using Graph Neural Network 26 Apr 2021 AmitRoy7781/USTGCN/USTGCN.py 37945d6e9686e018 ran · honoured contract fingerprinted no licence file found · pointer only
Do We Really Need Deep Learning Models for Time Series Forecasting? 6 Jan 2021 Daniela-Shereen/GBRT-for-TSF/XGBoost_(W-b)/Univariate/xgboostWB_electricity.py c0bd5bb363200341 ran · honoured contract fingerprinted no licence file found · pointer only
Learning Sub-Patterns in Piecewise Continuous Functions 29 Oct 2020 AnastasisKratsios/Architopes_Semisupervised/GET_FFNN_is_ADAM/Helper_Functions.py d0eef109b190c641 unverified MIT (permissive)
DeepXDE: A deep learning library for solving differential equations 10 Jul 2019 PhysicsTeacher13/Deepxde/deepxde/losses.py b6b3f1e69c63519d unverified Apache-2.0 (permissive)
DeepXDE: A deep learning library for solving differential equations 10 Jul 2019 yiwang89/lululxvi-deepxde/deepxde/metrics.py 7685754d1df284cc unverified Apache-2.0 (permissive)
Multitask learning and benchmarking with clinical time series data 22 Mar 2017 Dongximing/Mimic3/mimic3models/metrics.py bf861a65a6b445b6 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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