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MSE

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

MSE appears in the code Syntology harvested for 28 papers, as 22 distinct code bodies found in 30 places (a place is one code body under one paper). At least one of them ran in 18 of the papers; 11 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 MSE 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 13 of the 22 distinct code bodies named MSE; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

3ran · honoured contract
2ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
8ran
9unverified
11fingerprinted

Licence is a property of each copy, so it is counted per place: 14 of the 30 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

28 papers shown of 28, newest first; 30 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 6 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
Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization added by Syntology 2026-09 (from id) dasol-yoon/bott/bott/loss.py 8af5b00182642ca0 unverified no licence file found · pointer only
Structure-preserving uncertainty quantification for GENERIC dynamics added by Syntology 2026-08 (from id) Crunch-UQ4MI/neuraluq/neuraluq/metrics.py 56aa7fba8f7ea166 ran fingerprinted no licence file found · pointer only
Random test functions, $H^{-1}$ norm equivalence, and stochastic variational physics-informed neural networks added by Syntology 2026-05 (from id) dmarcondes/JINNAX/jinnax/nn.py 280eb0974866d37c ran · violated contract fingerprinted no licence file found · pointer only
Differentiable latent structure discovery for interpretable forecasting in clinical time series added by Syntology 2026-04 (from id) yalavarthivk/GraFITi/train_grafiti.py 363b7a0690754d6a ran no licence file found · pointer only
Differentiable latent structure discovery for interpretable forecasting in clinical time series added by Syntology 2026-04 (from id) yalavarthivk/GraFITi/baseline_experiments/train_linodenet.py a02367a938d20d4d ran fingerprinted no licence file found · pointer only
QUITOBENCH: A High-Quality Open Time Series Forecasting Benchmark added by Syntology 2026-03 (from id) alipay/quito/quito/metrics.py 2136500bcdbd55d3 unverified MIT (permissive)
CloDS: Visual-Only Unsupervised Cloth Dynamics Learning in Unknown Conditions added by Syntology 2026-02 (from id) whynot-zyl/CloDS/gaussian-mesh-splatting_node/NVS.py c2bfee96fb97d16c unverified no licence file found · pointer only
Data-driven Precipitation Nowcasting Using Satellite Imagery 16 Dec 2024 seominseok0429/data-driven-precipitation-nowcasting-using-satellite-imagery/metrics.py fd24f130e74dac73 unverified no licence file found · pointer only
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting 17 May 2024 xdzhelheim/himnet/lib/metrics.py 0a7d2992d05685eb ran fingerprinted no licence file found · pointer only
Topology-Informed Graph Transformer 3 Feb 2024 leemingo/cy2mixer/lib/metrics.py 0a7d2992d05685eb ran fingerprinted no licence file found · pointer only
Large Pre-trained time series models for cross-domain Time series analysis tasks 19 Nov 2023 adityalab/samay/src/samay/metric.py bddb4a39908fde27 ran fingerprinted Apache-2.0 (permissive)
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning 7 Nov 2023 RolnickLab/ClimateSet/emulator/src/core/metrics.py 0adfedc7b0db782c ran fingerprinted GPL-3.0 (copyleft) · pointer only
Generalization in diffusion models arises from geometry-adaptive harmonic representations 4 Oct 2023 LabForComputationalVision/memorization_generalization_in_diffusion_models/code/quality_metrics_func.py eb15c404ffac080f ran fingerprinted MIT (permissive)
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning 20 Jun 2023 chengtan9907/simvpv2/openstl/core/metrics.py c2bfee96fb97d16c unverified Apache-2.0 (permissive)
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization 9 Mar 2023 vanderschaarlab/tangos/src/tangos/losses.py 85e29a94928ecdaa unverified BSD-3-Clause (permissive)
Learning multi-scale local conditional probability models of images 6 Mar 2023 labforcomputationalvision/local-probability-models-of-images/code/quality_metrics_func.py eb15c404ffac080f ran fingerprinted MIT (permissive)
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction 11 Feb 2023 wz16/concernet/train_contrastive_conservation.py 47e5596498a1fdfc ran · honoured contract fingerprinted MIT (permissive)
Multi-Scale Memory-Based Video Deblurring 6 Apr 2022 jibo27/MemDeblur/train/loss.py 4e215f323ed97be2 ran MIT (permissive)
Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring 9 Dec 2021 xjtu-cvlab-lowlevel/rnn-mbp/train/loss.py 4e215f323ed97be2 ran no licence file found · pointer only
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations 8 Oct 2021 keiradams/chiro/model/optimization_functions.py 5358dfd3d26cc604 unverified MIT (permissive)
Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Network 30 Jun 2021 zzh-tech/ESTRNN/train/loss.py 4e215f323ed97be2 ran MIT (permissive)
Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation 10 Jun 2021 ai-secure/psba/src/main_pytorch_multi.py b3373b027f45777c ran · honoured contract fingerprinted no licence file found · pointer only
Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives 14 Apr 2021 hazimehh/l0group/bnb/HelperFuncs.py 87c3966085fe4eeb ran · honoured contract fingerprinted no licence file found · pointer only
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks 25 Feb 2021 identical code first harvested elsewhere b3373b027f45777c ran · honoured contract fingerprinted licence of this copy not recorded
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms 4 Nov 2020 johertrich/Proximal_Neural_Networks/core/stiefel_network.py 775e0de394eac78a ran · violated contract fingerprinted MIT (permissive)
Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise 29 Aug 2020 anncollin/AnomalyDetection-Keras/Models/Losses.py cd3673bd44747ec7 unverified Apache-2.0 (permissive)
arXiv:ijcai2025_0372 cwang-nus/DOL/utils/metrics.py bb33abd35aabfa4d unverified MIT (permissive)
arXiv:aaai_25976 deepkashiwa20/MegaCRN/model/metrics.py 0a7d2992d05685eb ran fingerprinted MIT (permissive)
arXiv:aaai_25976 deepkashiwa20/MegaCRN/model_EXPYTKY/metrics.py 1ede8e979a80e0d2 unverified MIT (permissive)
arXiv:Li_Met2Net_A_Decoupled_Two-Stage_Spatio-Temporal_Forecasting_Model_for_Complex_Meteorological_ICCV_2025_paper ShremG/Met2Net/openstl/core/metrics.py c2bfee96fb97d16c 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