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train_net

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

train_net appears in the code Syntology harvested for 9 papers, as 9 distinct code bodies found in 11 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 train_net 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 9 distinct code bodies named train_net; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
0ran
8unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 2 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

9 papers shown of 9, 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 1 papers added by Syntology; 2 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
ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems added by Syntology 2026-06 (from id) veronicasaz/RL_bridgedCluster/TrainRL.py 1a8b954d9dc9dccf unverified no licence file found · pointer only
Exploiting Label Skews in Federated Learning with Model Concatenation 11 Dec 2023 sjtudyq/fedconcat/experiments-fedconcat-id.py 2335d6ae7b4dde0f unverified MIT (permissive)
Exploiting Label Skews in Federated Learning with Model Concatenation 11 Dec 2023 sjtudyq/fedconcat/experiments-FeSEM.py a7ab2dc72d80b745 unverified MIT (permissive)
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis 18 Aug 2023 Sungwon-Han/FEDCPA/main_targeted_attack.py 9105203324a665f9 unverified no licence file found · pointer only
Synaptic Weight Distributions Depend on the Geometry of Plasticity 30 May 2023 romanpogodin/synaptic-weight-distr/linear_regression.py 617e0e99e16d5996 ran · our draft was wrong MIT (permissive)
FedTP: Federated Learning by Transformer Personalization 3 Nov 2022 zhyczy/fedtp/methods/method.py db0e6a41960059ed unverified MIT (permissive)
DC3: A learning method for optimization with hard constraints 25 Apr 2021 locuslab/DC3/method.py c8419695db89b99f unverified Apache-2.0 (permissive)
Federated Learning on Non-IID Data Silos: An Experimental Study 3 Feb 2021 eleanor-w/kci_for_fl/experiments.py 54a7795b20263264 unverified MIT (permissive)
arXiv:ijcai2024_0457 LonelyMoonDesert/FNR-FL/draw_noisy_image.py ed9c1f8baf279118 unverified MIT (permissive)
arXiv:aaai_29063 sjtudyq/FedConcat/experiments-fedconcat-id.py 2335d6ae7b4dde0f unverified MIT (permissive)
arXiv:aaai_29063 sjtudyq/FedConcat/experiments-FeSEM.py a7ab2dc72d80b745 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