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conv1d

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

conv1d appears in the code Syntology harvested for 31 papers, as 24 distinct code bodies found in 34 places (a place is one code body under one paper). At least one of them ran in 3 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 conv1d 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 3 of the 24 distinct code bodies named conv1d; 21 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
2ran
21unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 5 of the 34 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

31 papers shown of 31, newest first; 34 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; 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
CRA-PCN: Point Cloud Completion with Intra- and Inter-level Cross-Resolution Transformers 3 Jan 2024 easyry/cra-pcn/pointnet_utils/tf_util.py 7aab9e14068166d3 unverified no licence file found · pointer only
PHG-Net: Persistent Homology Guided Medical Image Classification 28 Nov 2023 yaoppeng/topoclassification/models/pointnet/layers_tf.py af107b37def4cf67 unverified no licence file found · pointer only
Microscaling Data Formats for Deep Learning 16 Oct 2023 microsoft/microxcaling/mx/convolution.py a43498acc45e8747 unverified MIT (permissive)
Generalized Few-Shot Point Cloud Segmentation Via Geometric Words 20 Sep 2023 Pixie8888/GFS-3DSeg_GWs/model/capl.py 003077f789923ed1 ran · metamorphic tier: deterministic fingerprinted MIT (permissive)
GridPull: Towards Scalability in Learning Implicit Representations from 3D Point Clouds 25 Aug 2023 chenchao15/GridPull/tf_util.py 054f0bfff19d6c70 ran no licence file found · pointer only
Unsupervised Inference of Signed Distance Functions from Single Sparse Point Clouds without Learning Priors 25 Mar 2023 chenchao15/NeuralTPS/tf_util.py 7aab9e14068166d3 unverified MIT (permissive)
Unit Scaling: Out-of-the-Box Low-Precision Training 20 Mar 2023 graphcore-research/unit-scaling-demo/scmm/uscale/ops.py 922e7a65963e6b06 unverified MIT (permissive)
DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders 22 Dec 2022 piddnad/ddcolor/basicsr/archs/ddcolor_arch_utils/unet.py 0dcc55ae179ff89e unverified Apache-2.0 (permissive)
Trajectory Prediction with Graph-based Dual-scale Context Fusion 2 Nov 2021 hkust-aerial-robotics/dsp/networks/network_utils.py daceb448ca90f5e5 unverified MIT (permissive)
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning 21 May 2021 azuki-miho/RFCR/RandLA_Net_S3DIS/helper_tf_util.py 9ed4be924ecef796 unverified MIT (permissive)
An optical neural network using less than 1 photon per multiplication 27 Apr 2021 mcmahon-lab/ONN-QAT-SQL/main_mnist_mlp_QAT.py dc88ecd8210a7392 unverified CC-BY-4.0 · pointer only
One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation 6 Apr 2021 PointCloudYC/SQN_tensorflow/helper_tf_util.py 9ed4be924ecef796 unverified MIT (permissive)
Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains 15 Oct 2020 RUC-WSM/WD-Match/src/model.py e97b2113436b499c unverified no licence file found · pointer only
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges 7 Sep 2020 QingyongHu/SensatUrban/tf_util.py 9ed4be924ecef796 unverified MIT (permissive)
Pillar-based Object Detection for Autonomous Driving 20 Jul 2020 WangYueFt/pillar-od/network.py ae08fa5021cce887 unverified MIT (permissive)
RPM-Net: Recurrent Prediction of Motion and Parts from Point Cloud 26 Jun 2020 Salingo/RPM-Net/code/utils/tf_util.py 18d51d8d06002af3 unverified MIT (permissive)
ABCNet: An attention-based method for particle tagging 2020-01 (from id) ViniciusMikuni/ABCNet/utils/tf_util.py 04c1ecf4b95c0fa8 unverified MIT (permissive)
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks 27 Dec 2019 labRadioVision/federated/tensorflow1_implementations/federated_onraspberry_CNN_realtime.py 7e6f6769469edc1a unverified MIT (permissive)
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks 27 Dec 2019 labRadioVision/federated/tensorflow1_implementations/federated_sample_2NN_CFA-GE.py eae7a87c998d5871 unverified MIT (permissive)
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks 27 Dec 2019 labRadioVision/federated/tensorflow1_implementations/federated_sample_CNN_CFA-GE.py 731286ea3e1dd0c1 unverified MIT (permissive)
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation 24 Sep 2019 rosinality/ocr-pytorch/model.py ab8dda773f3d5789 ran · our draft was wrong MIT (permissive)
Once-for-All: Train One Network and Specialize it for Efficient Deployment 26 Aug 2019 MaximIntegratedAI/ai8x-synthesis/izer/compute.py d2876e3d44cca1e5 unverified Apache-2.0 (permissive)
CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages 27 Mar 2019 Kyubyong/css10/tacotron/modules.py 6f9a221306ef60fb unverified Apache-2.0 (permissive)
Path-Invariant Map Networks 31 Dec 2018 zaiweizhang/path_invariance_map_network/tf_util.py 18d51d8d06002af3 unverified BSD-3-Clause (permissive)
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud 8 Dec 2018 ericyi/GSPN/utils/tf_util.py 798f68da5db33b27 unverified MIT (permissive)
TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes 30 Nov 2018 hjwdzh/TextureNet/src/models/tf_util.py 18d51d8d06002af3 unverified MIT (permissive)
Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN 19 Nov 2018 voidrank/Geo-CNN/models/tf_util.py 18d51d8d06002af3 unverified Apache-2.0 (permissive)
Generating 3D Adversarial Point Clouds 19 Sep 2018 LONG-9621/Generating-3D-Adversarial-Point-Clouds/utils/tf_util.py 7aab9e14068166d3 unverified MIT (permissive)
Self-Attention Generative Adversarial Networks 21 May 2018 sdoria/SimpleSelfAttention/xresnet.py 9529ce8993bceed1 unverified Apache-2.0 (permissive)
Local Spectral Graph Convolution for Point Set Feature Learning 15 Mar 2018 fate3439/LocalSpecGCN/utils/tf_util.py 118d5fb0c3a178ea unverified MIT (permissive)
Tacotron: Towards End-to-End Speech Synthesis 29 Mar 2017 Kyubyong/tacotron/modules.py 6f9a221306ef60fb unverified Apache-2.0 (permissive)
Tacotron: Towards End-to-End Speech Synthesis 29 Mar 2017 andabi/deep-voice-conversion/modules.py c5f26d8500f4124f unverified MIT (permissive)
arXiv:Wang_PWCLO-Net_Deep_LiDAR_Odometry_in_3D_Point_Clouds_Using_Hierarchical_CVPR_2021_paper IRMVLab/PWCLONet/utils/tf_util.py 18d51d8d06002af3 unverified MIT (permissive)
arXiv:136620053 Tianxinhuang/PCDNet/tf_util.py 04c1ecf4b95c0fa8 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".

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