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Coord2dPosEncoding

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

Coord2dPosEncoding appears in the code Syntology harvested for 17 papers, as 3 distinct code bodies found in 17 places (a place is one code body under one paper). At least one of them ran in 1 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 Coord2dPosEncoding 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 1 of the 3 distinct code bodies named Coord2dPosEncoding; 2 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 11 of the 17 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

17 papers shown of 17, newest first; 17 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 5 papers added by Syntology; 1 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
CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts added by Syntology 2026-06 (from id) liubolab/CausalMoE/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting added by Syntology 2026-04 (from id) jafarbakhshaliyev/TPS/time_series_forecasting/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting added by Syntology 2026-02 (from id) Meteor-Stars/SEMixer/layers/Embedding.py c3fc6992d1e467f3 unverified no licence file found · pointer only
Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency added by Syntology 2025-10 (from id) MazelTovy/AMRC/PatchTST/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters added by Syntology 2025-09 (from id) Luoauoa/ReNF/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified MIT (permissive)
arXiv:2506.23596 2025-06 (from id) KU-VGI/AP/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified Apache-2.0 (permissive)
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra 22 Feb 2025 azureleon1/molspectra/torchmdnet/models/SpecFormer_layers.py a82b47c227d5b5bc unverified no licence file found · pointer only
MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters 2 Oct 2024 lss-1138/SparseTSF/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified Apache-2.0 (permissive)
TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment 3 Jun 2024 chenxiliu-hnu/timecma/layers/TS_Pos_Enc.py c3fc6992d1e467f3 unverified no licence file found · pointer only
SST: Multi-Scale Hybrid Mamba-Transformer Experts for Long-Short Range Time Series Forecasting 23 Apr 2024 xiongxiaoxu/sst/layers/LWT_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling 20 Feb 2024 Levi-Ackman/Leddam/layers/Leddam.py 50720c9e7fed4f64 ran no licence file found · pointer only
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators 31 Jan 2024 SJTU-DMTai/LIFT/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
Multi-resolution Time-Series Transformer for Long-term Forecasting 7 Nov 2023 Yitiann/MTST/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only
Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift 23 Oct 2023 half111/calibration_cds/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified MIT (permissive)
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting 10 Oct 2023 lss-1138/SegRNN/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified Apache-2.0 (permissive)
PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting 1 Oct 2023 Zeying-Gong/PatchMixer/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified MIT (permissive)
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer 9 Aug 2023 ACAT-SCUT/PETformer/layers/PatchTST_layers.py c3fc6992d1e467f3 unverified no licence file found · pointer only

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