Methods › Computer Vision › Likelihood-Based Generative Models › NICE › Papers where code ran, page 1
Non-linear Independent Component Estimation
NICE
Papers archive 2025-07-28
archive papers tagged: 22 · with a code link: 10 · where Syntology ran a sample: 3 (2 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (3 of 22 tagged: 2 with a run with no instrument failure, 1 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 3 of the 3 tagged papers where Syntology ran at least one harvested sample (2 with a run with no instrument failure, 1 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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The Devil is in the Labels: Noisy Label Correction for Robust Scene Graph Generation 7 Jun 2022 · 1 repository · arXiv:2206.03014Syntology 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) · 1 unverified (of 2 harvested samples) · 2 pointer-only (licence)
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Invariant Representation Learning for Treatment Effect Estimation 24 Nov 2020 · 1 repository · arXiv:2011.12379Syntology official (archive's flag): 1 ran · 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) · 1 unverified (of 3 harvested samples) · 3 pointer-only (licence)
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NICE: Non-linear Independent Components Estimation 30 Oct 2014 · 19 repositories · arXiv:1410.8516Syntology 24 ran (of which 16 constructed an object rather than computing a result; 19 with no instrument failure: 0 honoured, 0 violated, 19 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified (of 27 harvested samples)