Home › Code › ActivationLayer

ActivationLayer

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

ActivationLayer appears in the code Syntology harvested for 7 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 7 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 ActivationLayer 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 6 of the 8 distinct code bodies named ActivationLayer; 2 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 9 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

7 papers shown of 7, 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. 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
Advancing Parameter Efficiency in Fine-tuning via Representation Editing 23 Feb 2024 mlwu22/RED/model.py 7a6bbc394c0f5543 ran no licence file found · pointer only
Continual Learning: Forget-free Winning Subnetworks for Video Representations 19 Dec 2023 ihaeyong/pnr/model_nerv.py 878fd412e7a78234 ran · our draft was wrong MIT (permissive)
HNeRV: A Hybrid Neural Representation for Videos 5 Apr 2023 haochen-rye/hnerv/model_all.py 2798c7e0f39b709e ran · our draft was wrong no licence file found · pointer only
Scalable Neural Video Representations with Learnable Positional Features 13 Oct 2022 haochen-rye/nerv/model_nerv.py 878fd412e7a78234 ran · our draft was wrong no licence file found · pointer only
Scalable Neural Video Representations with Learnable Positional Features 13 Oct 2022 identical code first harvested elsewhere bab299b09f52a8de unverified licence of this copy not recorded
E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context 17 Jul 2022 kyleleey/E-NeRV/model/E_NeRV.py c8903a27f5af9ea1 ran · our draft was wrong no licence file found · pointer only
NeRV: Neural Representations for Videos 26 Oct 2021 identical code first harvested elsewhere 878fd412e7a78234 ran · our draft was wrong licence of this copy not recorded
NeRV: Neural Representations for Videos 26 Oct 2021 haochen-rye/NeRV/model_nerv.py bab299b09f52a8de unverified no licence file found · pointer only
Neural Additive Models: Interpretable Machine Learning with Neural Nets 29 Apr 2020 kherud/neural-additive-models-pt/nam/model.py 51c75dde5a5a0f26 ran no licence file found · pointer only
Neural Additive Models: Interpretable Machine Learning with Neural Nets 29 Apr 2020 nickfrosst/neural_additive_models/models.py 546b56723399f9fe ran no licence file found · pointer only
Neural Additive Models: Interpretable Machine Learning with Neural Nets 29 Apr 2020 google-research/google-research/neural_additive_models/models.py 9e20b229f2c0a6a3 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