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sparse_dropout

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

sparse_dropout appears in the code Syntology harvested for 30 papers, as 16 distinct code bodies found in 31 places (a place is one code body under one paper). At least one of them ran in 2 of the papers; 1 of the code bodies carries 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 sparse_dropout 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 2 of the 16 distinct code bodies named sparse_dropout; 14 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
1ran
14unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 31 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

30 papers shown of 30, newest first; 31 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; 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
PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning 27 Feb 2024 hkuds/promptmm/codes/Models.py 94aa457af38d3535 ran no licence file found · pointer only
Combating Bilateral Edge Noise for Robust Link Prediction 2 Nov 2023 flyingdoog/PTDNet/NeuralSparse/layers.py 107e7afdd93ee0b4 unverified no licence file found · pointer only
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation 16 Feb 2023 hkuds/lightgcl/model.py 1115b743f293ce3e unverified no licence file found · pointer only
DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems 8 Oct 2022 dimesteam/dimes/MIS/solvers/intel_treesearch/NPHard/gcn/models.py 295f9a13c181045b unverified MIT (permissive)
Adversarial Attack on Large Scale Graph 8 Sep 2020 EdisonLeeeee/SGAttack/src/classifier/gcn.py 81be8a5f4732fe52 unverified MIT (permissive)
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters 19 Aug 2020 safe-graph/dgfraud-tf2/layers/layers.py fcf4f04027e8dde1 unverified Apache-2.0 (permissive)
SkeletonNet: A Topology-Preserving Solution for Learning Mesh Reconstruction of Object Surfaces from RGB Images 13 Aug 2020 tangjiapeng/SkeletonNet/SkeGCNN/deformation/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs 20 Jun 2020 tkipf/gcn/gcn/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Knowledge Embedding Based Graph Convolutional Network 12 Jun 2020 Maysir/GEM-GCN/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Machine Learning on Graphs: A Model and Comprehensive Taxonomy 7 May 2020 google/gcnn-survey-paper/utils/model_utils.py ddcf68e913917c2b unverified Apache-2.0 (permissive)
Scalable Attack on Graph Data by Injecting Vicious Nodes 22 Apr 2020 wangjh-github/AFGSM/GCN.py 374efabcab5ab5b1 unverified Apache-2.0 (permissive)
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback 23 Feb 2020 chadwang2012/SetRank/sparse-Deep-SetRank.py 6224fad646592bac unverified no licence file found · pointer only
Unifying Graph Convolutional Neural Networks and Label Propagation 17 Feb 2020 achalagarwal/gcn-lpa/src/layers.py cd61377ca3953238 unverified MIT (permissive)
Unifying Graph Convolutional Neural Networks and Label Propagation 17 Feb 2020 hwwang55/GCN-LPA/src/layers.py ce452a33739aaed9 unverified MIT (permissive)
Tensor Graph Convolutional Networks for Text Classification 12 Jan 2020 thumlp/tensorgcn/TGCN_2layers/layers.py 81be8a5f4732fe52 unverified no licence file found · pointer only
Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation 20 Nov 2019 nju-websoft/AliNet/code/gnn/gcn/layers.py 53639130076fc405 unverified MIT (permissive)
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction 5 Nov 2019 CRIPAC-DIG/GraphAIR/tensorflow_code/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation 5 Aug 2019 walsvid/Pixel2MeshPlusPlus/modules/layers.py 81be8a5f4732fe52 unverified BSD-3-Clause (permissive)
Deep Bayesian Optimization on Attributed Graphs 31 May 2019 csjtx1021/DGBO/gcn/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Unsupervised Community Detection with Modularity-Based Attention Model 20 May 2019 Ivanopolo/modnet/kipf/layers.py 81be8a5f4732fe52 unverified Apache-2.0 (permissive)
Adversarial Attacks on Graph Neural Networks via Meta Learning 22 Feb 2019 danielzuegner/gnn-meta-attack/metattack/meta_gradient_attack.py 81be8a5f4732fe52 unverified MIT (permissive)
Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification 13 Feb 2019 CRIPAC-DIG/H-GCN/tensorflow_code/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Label Efficient Semi-Supervised Learning via Graph Filtering 28 Jan 2019 liqimai/Efficient-SSL/gcn/layers.py 87228419e7730a39 unverified MIT (permissive)
Bayesian graph convolutional neural networks for semi-supervised classification 27 Nov 2018 huawei-noah/BGCN/src/layers.py 81be8a5f4732fe52 unverified MIT recorded; this copy not marked cleared · pointer only
A Recurrent Graph Neural Network for Multi-Relational Data 5 Nov 2018 bioannidis/adaptive_recurrent_graph_neural_network/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
Predict then Propagate: Graph Neural Networks meet Personalized PageRank 14 Oct 2018 klicperajo/ppnp/ppnp/tensorflow/utils.py 3b270c601a03ed8c unverified MIT (permissive)
Adversarial Attacks on Neural Networks for Graph Data 21 May 2018 danielzuegner/nettack/nettack/GCN.py 81be8a5f4732fe52 unverified MIT (permissive)
Stochastic Training of Graph Convolutional Networks with Variance Reduction 29 Oct 2017 thu-ml/stochastic_gcn/gcn/layers.py 89f0c89b676a4a82 unverified MIT (permissive)
Semi-Supervised Classification with Graph Convolutional Networks 9 Sep 2016 nieci2024/pyglcn/glcn/layers.py 3df97104adae129f ran · our draft was wrong fingerprinted MIT (permissive)
Revisiting Semi-Supervised Learning with Graph Embeddings 29 Mar 2016 asarigun/la-gcn-tensorflow/layers.py 81be8a5f4732fe52 unverified MIT (permissive)
arXiv:aaai_20873 RICE-EIC/Early-Bird-GCN/gcn/layers.py 81be8a5f4732fe52 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