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mae

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

mae appears in the code Syntology harvested for 41 papers, as 30 distinct code bodies found in 41 places (a place is one code body under one paper). At least one of them ran in 20 of the papers; 10 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 mae 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 30 distinct code bodies named mae; 19 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
2ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
7ran
19unverified
10fingerprinted

Licence is a property of each copy, so it is counted per place: 12 of the 41 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

41 papers shown of 41, newest first; 41 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 8 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
Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets added by Syntology 2026-09 (from id) Kimalice/Toward-Explainable-and-Policy-Aware-AI-for-Carbon-Credit-Price-Prediction/paxcarbonnet/metrics.py a1424f0703cded50 unverified licence not identified · pointer only
An Empirical Benchmark of Deep Time-Series Models for Smart Meter Energy Forecasting added by Syntology 2026-08 (from id) behnazkavoosi/Energy-Time-Series-Library/compute_metrics.py 2c88fa85214e7d48 ran fingerprinted MIT (permissive)
TS-Fault: Benchmarking Time Series Forecasters Against Structural Faults added by Syntology 2026-06 (from id) Ray-zyy/TS-Fault/eval_foundation_phase1.py 2c88fa85214e7d48 ran fingerprinted no licence file found · pointer only
Conveyance: A Versatile Framework for Learning in Structured Class Spaces added by Syntology 2026-05 (from id) ZKI-PH-ImageAnalysis/Conveyance/Annotation-Bias/loss.py b9b020472d1ef906 ran MIT (permissive)
Revisiting Chebyshev Polynomial and Anisotropic RBF Models for Tabular Regression added by Syntology 2026-02 (from id) gerberl/poly-erbf-benchmark/perbf/evaluation/metrics.py c859d072a2ab4fd7 unverified MIT (permissive)
Thermodynamic assessment of machine learning models for solid-state synthesis prediction added by Syntology 2026-02 (from id) kaist-amsg/Synthesizability-PU-CGCNN/main_PU_learning.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted no licence file found · pointer only
Rethinking Recurrent Neural Networks for Time Series Forecasting: A Reinforced Recurrent Encoder with Prediction-Oriented Proximal Policy Optimization added by Syntology 2026-01 (from id) Laixin233/-Reinforced-Encoder/task/metric.py 12640a5c31d3e0fe unverified no licence file found · pointer only
Self-Supervised Dynamical System Representations for Physiological Time-Series added by Syntology 2025-12 (from id) yuqinie98/PatchTST/PatchTST_self_supervised/src/metrics.py 4d345bf5bfa84ace unverified Apache-2.0 (permissive)
xLSTMTime : Long-term Time Series Forecasting With xLSTM 14 Jul 2024 muslehal/xLSTMTime/src/metrics.py 4d345bf5bfa84ace unverified MIT (permissive)
Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration 26 Jun 2024 kangliao929/noise-da/models/metric.py 0570fbc1e2582ae7 ran fingerprinted licence not identified · pointer only
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models 5 Jun 2024 layer6ai-labs/flipd/lid/evaluation/lid_evaluation.py 2dc9f8e6f1b3636e ran · violated contract fingerprinted no licence file found · pointer only
Con-CDVAE: A method for the conditional generation of crystal structures 2024-03 (from id) cyye001/con-cdvae/cgcnn/predict.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted MIT (permissive)
A path-dependent PDE solver based on signature kernels 2024-03 (from id) crispitagorico/sigppde/utils.py ab6e258bbc18e37d ran fingerprinted MIT (permissive)
Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting 8 Jan 2024 pengxin-guo/adcsd/libcity/evaluator/eval_funcs.py adfbb8bc32262202 ran fingerprinted no licence file found · pointer only
A foundation model for atomistic materials chemistry 2024-01 (from id) arosen93/qmof/machine_learning/cgcnn/predict.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted MIT (permissive)
Multi-scale Reconstruction of Turbulent Rotating Flows with Generative Diffusion Models 2023-12 (from id) smartturb/palette-turb/models/metric.py 0570fbc1e2582ae7 ran fingerprinted MIT (permissive)
Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models 11 Oct 2023 ryliu68/CDMA/models/metric.py 0570fbc1e2582ae7 ran fingerprinted MIT (permissive)
DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images 8 Aug 2023 xavierjiezou/diffcr/models/metric.py 0570fbc1e2582ae7 ran fingerprinted no licence file found · pointer only
BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning 27 Jul 2023 hpcforge/bubbleml/sciml/op_lib/metrics.py 182909793fbe5044 ran fingerprinted no licence file found · pointer only
Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images 14 Jul 2023 lilygeorgescu/mae-medical-anomaly-detection/evaluate_sup.py 74df7139a58f71a6 ran · violated contract fingerprinted licence not identified · pointer only
PIGEON: Predicting Image Geolocations 11 Jul 2023 LukasHaas/PIGEON/evaluation/metrics.py b3cad4ecdab12eef ran fingerprinted licence not identified · pointer only
Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis 16 Jun 2023 mitchellostrow/dsa/DSA/stats.py 43a5b3592b84536d unverified MIT (permissive)
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning 2 Jun 2023 THUNLP-MT/GET/evaluate.py 55dc4516b218bc5e unverified MIT (permissive)
GSURE-Based Diffusion Model Training with Corrupted Data 22 May 2023 bahjat-kawar/gsure-diffusion/generate.py f421021f6a45c9a4 ran · honoured contract fingerprinted no licence file found · pointer only
LibCity: A Unified Library Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction 27 Apr 2023 libcity/bigscity-libcity/libcity/evaluator/eval_funcs.py dd2102b030c94016 unverified Apache-2.0 (permissive)
A Benchmark and a Baseline for Robust Multi-view Depth Estimation 13 Sep 2022 lmb-freiburg/robustmvd/rmvd/loss/utils.py 17be877e869b59a5 unverified Apache-2.0 (permissive)
Musika! Fast Infinite Waveform Music Generation 18 Aug 2022 marcoppasini/musika/losses.py f447aaedd81df24c unverified MIT (permissive)
Learning Deep Time-index Models for Time Series Forecasting 13 Jul 2022 salesforce/deeptime/utils/metrics.py f5e904e06587dc6a unverified BSD-3-Clause (permissive)
Accelerating Material Design with the Generative Toolkit for Scientific Discovery 8 Jul 2022 gt4sd/gt4sd-core/src/gt4sd/training_pipelines/cgcnn/core.py 13690cec3ee4ba4f unverified MIT (permissive)
What Information is Necessary and Sufficient to Predict Materials Properties using Machine Learning? 2022-06 (from id) pv-lab/compstruct/main_cgcnn.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted MIT (permissive)
Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data 15 Dec 2021 RetroCirce/Zero_Shot_Audio_Source_Separation/losses.py b7cd9d2f3d4b3669 unverified MIT (permissive)
Long-Range Transformers for Dynamic Spatiotemporal Forecasting 24 Sep 2021 qdata/spacetimeformer/spacetimeformer/eval_stats.py c8124414b7e9de1b unverified MIT (permissive)
CrysXPP:An Explainable Property Predictor for Crystalline Materials 2021-04 (from id) iitkgpaiforscience/crysxpp/src/prop.py be7ec3c87b0c2292 unverified MIT (permissive)
An Experimental Review on Deep Learning Architectures for Time Series Forecasting 22 Mar 2021 pedrolarben/TimeSeriesForecasting-DeepLearning/experiments/metrics.py bbb210993c0eedbe unverified MIT (permissive)
Deep learning the spanwise-averaged Navier--Stokes equations 2020-08 (from id) b-fg/SANSpy/sanspy/losses.py 9ba5975605c85b37 unverified MIT (permissive)
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey 21 Apr 2020 potosnakw/neuralforecast/neuralforecast/losses/numpy.py 84033b84cec70d7a unverified Apache-2.0 (permissive)
Meta Pseudo Labels 23 Mar 2020 usccolumbia/tsdnn/predict.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted MIT (permissive)
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals 2018-12 (from id) materialsvirtuallab/megnet/megnet/utils/metrics.py 7cd70353cde137d0 unverified BSD-3-Clause (permissive)
Relational inductive biases, deep learning, and graph networks 4 Jun 2018 davidtangGT/MEGNET/megnet/utils/metrics.py 7cd70353cde137d0 unverified BSD-3-Clause (permissive)
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties 2017-10 (from id) txie-93/cgcnn/predict.py 8d28ce13cc82e55f ran · our draft was wrong fingerprinted MIT (permissive)
NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring 2014-04 (from id) nilmtk/nilmtk/nilmtk/losses.py 9ac0edff092e856a unverified Apache-2.0 (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