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get_activation_function

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

get_activation_function appears in the code Syntology harvested for 17 papers, as 15 distinct code bodies found in 17 places (a place is one code body under one paper). At least one of them ran in 8 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 get_activation_function 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 7 of the 15 distinct code bodies named get_activation_function; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
5ran · our draft was wrong
0ran · fixture could not drive it
2ran
8unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 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 1 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
Cross-Subject Modeling for Widefield Calcium Imaging via Atlas-Aligned Spatiotemporal Tokenization added by Syntology 2026-07 (from id) ShanechiLab/WiCAT/wicat/utility/torch_utils.py 7b72b4d4ea787ea2 ran licence not identified · pointer only
Temporal-Difference Variational Continual Learning 10 Oct 2024 luckeciano/TD-VCL/modules/td_vcl.py cbb32079ed8b32f4 ran · our draft was wrong no licence file found · pointer only
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning 30 Sep 2024 iandrover/ccl-neurips24/models/layers.py 2c3e90745ee492a6 ran · our draft was wrong MIT (permissive)
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning 21 Jun 2024 seai-lab/torchspatial/main/module.py 063ddd72ea995d8a ran MIT (permissive)
Deep Bayesian Active Learning for Preference Modeling in Large Language Models 14 Jun 2024 luckeciano/BAL-PM/uqlrm/modules/mc_dropout_reward_mlp.py cbb32079ed8b32f4 ran · our draft was wrong no licence file found · pointer only
Disentangling and Integrating Relational and Sensory Information in Transformer Architectures 26 May 2024 awni00/abstract_transformer/dual_attention_transformer.py 074ed3e1882dc275 ran · our draft was wrong MIT (permissive)
CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects 2024-03 (from id) contact-non-prehensile/corn/pkm/src/pkm/models/rl/nets.py a1aa7704932ab281 ran · our draft was wrong MIT (permissive)
Novel Class Discovery: an Introduction and Key Concepts 22 Feb 2023 orange-opensource/practicalncd/src/utils.py e8209885c480bc17 unverified MIT (permissive)
Federated Causal Discovery From Interventions 7 Nov 2022 aminabyaneh/fed-cd/causal_discovery/multivariable_mlp.py 7684c39f7ed75a94 unverified MIT (permissive)
Towards General-Purpose Representation Learning of Polygonal Geometries 29 Sep 2022 gengchenmai/polygon_encoder/polygoncode/polygonembed/module.py 0bb68fd06ed2366f unverified Apache-2.0 (permissive)
Autoencoder Attractors for Uncertainty Estimation 1 Apr 2022 stevecruz/icpr2022-autoencoder-attractors/model.py 2ca7c06dee9dff95 unverified MIT (permissive)
Molecular Contrastive Learning with Chemical Element Knowledge Graph 1 Dec 2021 ZJU-Fangyin/KCL/code/model/model_utils.py fb4d7a9cb6a20e63 unverified MIT (permissive)
CLIP: Cheap Lipschitz Training of Neural Networks 23 Mar 2021 TimRoith/CLIP/models.py 36a0785fcf9184b0 unverified MIT (permissive)
Implicit Neural Representations with Periodic Activation Functions 17 Jun 2020 linusnie/diffcd/diffcd/networks.py c1c479c977b6d4f1 unverified Apache-2.0 (permissive)
SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting 25 Apr 2020 gengchenmai/se-kge/graphqa/netquery/module.py 0bb68fd06ed2366f unverified Apache-2.0 (permissive)
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning 4 Sep 2019 smsharma/mining-for-substructure-lens/inference/utils.py e5bf3661ec3f3bb9 unverified MIT (permissive)
DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation 17 Apr 2019 uncbiag/DeepAtlas/lib/network_factory/unets.py d5e6ccb754083be5 ran · our draft was wrong 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".

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