Methods › General › Initialization › Xavier Initialization › Papers where code ran, page 1
Xavier Initialization
Papers archive 2025-07-28
archive papers tagged: 121 · with a code link: 51 · where Syntology ran a sample: 12 (7 with a run with no instrument failure, 5 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (12 of 121 tagged: 7 with a run with no instrument failure, 5 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 1 of 1: papers 1 to 12 of the 12 tagged papers where Syntology ran at least one harvested sample (7 with a run with no instrument failure, 5 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.
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Object Detection with Spiking Neural Networks on Automotive Event Data 9 May 2022 · 1 repository · arXiv:2205.04339Syntology official (archive's flag): 1 ran · 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)
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WaveGrad: Estimating Gradients for Waveform Generation 2 Sep 2020 · 7 repositories · arXiv:2009.00713Syntology 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples) · 1 pointer-only (licence)
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Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network 17 Jan 2020 · 1 repository · arXiv:2001.06268Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified (of 11 harvested samples)
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Mish: A Self Regularized Non-Monotonic Activation Function 23 Aug 2019 · 9 repositories · arXiv:1908.08681Syntology official (archive's flag): 6 ran · 9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified (of 12 harvested samples) · 1 pointer-only (licence)
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HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision 29 Apr 2019 · 1 repository · arXiv:1905.03696Syntology official: harvested, nothing ran · 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) · 2 unverified (of 3 harvested samples) · 3 pointer-only (licence)
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ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs 27 Feb 2019 · 5 repositories · arXiv:1902.10298Syntology 4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified (of 7 harvested samples) · 1 pointer-only (licence)
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Bag of Tricks for Image Classification with Convolutional Neural Networks 4 Dec 2018 · 28 repositories · arXiv:1812.01187Syntology community repositories only · 11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified (of 15 harvested samples) · 5 pointer-only (licence)
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Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex 6 Jun 2018 · 1 repository · arXiv:1806.01845Syntology official (archive's flag): 4 ran · 4 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; 3 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples) · 4 pointer-only (licence)
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SqueezeNext: Hardware-Aware Neural Network Design 23 Mar 2018 · 8 repositories · arXiv:1803.10615Syntology 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)
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FractalNet: Ultra-Deep Neural Networks without Residuals 24 May 2016 · 4 repositories · arXiv:1605.07648Syntology 4 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; 4 where Syntology's instrument failed) · 2 unverified (of 6 harvested samples) · 1 pointer-only (licence)
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size 24 Feb 2016 · 59 repositories · arXiv:1602.07360Syntology community repositories only · 4 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; 4 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples) · 2 pointer-only (licence)
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Very Deep Convolutional Networks for Large-Scale Image Recognition 4 Sep 2014 · 305 repositories · arXiv:1409.1556Syntology 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)