Methods › General › Regularization › Dropout › Papers where code ran, page 37

Dropout

Papers archive 2025-07-28

archive papers tagged: 27,472 · with a code link: 12,129 · where Syntology ran a sample: 3,620 (3,044 with a run with no instrument failure, 576 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (3,620 of 27,472 tagged: 3,044 with a run with no instrument failure, 576 where every run was a failure of Syntology's instrument)

Syntology We ran code from the paper's repository; we did not isolate this method inside it.

Page 37 of 37: papers 3,601 to 3,620 of the 3,620 tagged papers where Syntology ran at least one harvested sample (3,044 with a run with no instrument failure, 576 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.

Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.

• Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
  9 Nov 2015 · 21 repositories · arXiv:1511.02680
  Syntology 6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 12 unverified (of 18 harvested samples)
• BinaryConnect: Training Deep Neural Networks with binary weights during propagations
  2 Nov 2015 · 5 repositories · arXiv:1511.00363
  Syntology community repositories only · 3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples) · 3 pointer-only (licence)
• Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
  1 Oct 2015 · 15 repositories · arXiv:1510.00149
  Syntology 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified (of 4 harvested samples) · 1 pointer-only (licence)
• Fast Algorithms for Convolutional Neural Networks
  30 Sep 2015 · 5 repositories · arXiv:1509.09308
  Syntology 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
• Tensorizing Neural Networks
  22 Sep 2015 · 4 repositories · arXiv:1509.06569
  Syntology community repositories only · 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample) · 1 pointer-only (licence)
• Deep Convolutional Networks on Graph-Structured Data
  16 Jun 2015 · 3 repositories · arXiv:1506.05163
  Syntology 7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 7 harvested samples)
• Teaching Machines to Read and Comprehend
  10 Jun 2015 · 12 repositories · arXiv:1506.03340
  Syntology community repositories only · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 2 harvested samples)
• Variational Dropout and the Local Reparameterization Trick
  8 Jun 2015 · 12 repositories · arXiv:1506.02557
  Syntology 5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified (of 6 harvested samples) · 5 pointer-only (licence)
• Learning both Weights and Connections for Efficient Neural Networks
  8 Jun 2015 · 8 repositories · arXiv:1506.02626
  Syntology 7 ran (of which 3 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified (of 8 harvested samples) · 3 pointer-only (licence)
• You Only Look Once: Unified, Real-Time Object Detection
  8 Jun 2015 · 144 repositories · arXiv:1506.02640
  Syntology 89 ran (of which 27 constructed an object rather than computing a result; 59 with no instrument failure: 4 honoured, 4 violated, 51 with no contract checked; 30 where Syntology's instrument failed) · 59 unverified (of 148 harvested samples) · 98 pointer-only (licence)
• Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
  6 Jun 2015 · 29 repositories · arXiv:1506.02142
  Syntology 4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 2 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples) · 4 pointer-only (licence)
• Cyclical Learning Rates for Training Neural Networks
  3 Jun 2015 · 53 repositories · arXiv:1506.01186
  Syntology official: no sample here; runs from other or unrecorded repositories · 15 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified (of 17 harvested samples) · 2 pointer-only (licence)
• Weight Uncertainty in Neural Networks
  20 May 2015 · 38 repositories · arXiv:1505.05424
  Syntology 12 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 4 honoured, 1 violated, 0 with no contract checked; 7 where Syntology's instrument failed) · 3 unverified (of 15 harvested samples) · 7 pointer-only (licence)
• Learning Deconvolution Network for Semantic Segmentation
  17 May 2015 · 5 repositories · arXiv:1505.04366
  Syntology 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 2 harvested samples) · 2 pointer-only (licence)
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
  11 Feb 2015 · 70 repositories · arXiv:1502.03167
  Syntology 19 ran (of which 5 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 5 where Syntology's instrument failed) · 2 unverified (of 21 harvested samples) · 5 pointer-only (licence)
• Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  6 Feb 2015 · 15 repositories · arXiv:1502.01852
  Syntology 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample) · 1 pointer-only (licence)
• Fully Convolutional Networks for Semantic Segmentation
  14 Nov 2014 · 51 repositories · arXiv:1411.4038
  Syntology 3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified (of 4 harvested samples) · 4 pointer-only (licence)
• Going Deeper with Convolutions
  17 Sep 2014 · 83 repositories · arXiv:1409.4842
  Syntology community repositories only · 34 ran (of which 19 constructed an object rather than computing a result; 30 with no instrument failure: 0 honoured, 0 violated, 30 with no contract checked; 4 where Syntology's instrument failed) · 8 unverified (of 42 harvested samples) · 21 pointer-only (licence)
• Recurrent Neural Network Regularization
  8 Sep 2014 · 21 repositories · arXiv:1409.2329
  Syntology community repositories only · 2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified (of 6 harvested samples) · 6 pointer-only (licence)
• Very Deep Convolutional Networks for Large-Scale Image Recognition
  4 Sep 2014 · 305 repositories · arXiv:1409.1556
  Syntology 81 ran (of which 0 constructed an object rather than computing a result; 71 with no instrument failure: 0 honoured, 0 violated, 71 with no contract checked; 10 where Syntology's instrument failed) · 41 unverified (of 122 harvested samples) · 8 pointer-only (licence)