Methods › General › Interpretability › Monte Carlo Dropout › Papers where code ran, page 1
Monte Carlo Dropout
Papers archive 2025-07-28
archive papers tagged: 202 · with a code link: 60 · where Syntology ran a sample: 14 (11 with a run with no instrument failure, 3 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (14 of 202 tagged: 11 with a run with no instrument failure, 3 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 14 of the 14 tagged papers where Syntology ran at least one harvested sample (11 with a run with no instrument failure, 3 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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Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging 11 Oct 2024 · 1 repository · arXiv:2410.09299Syntology official (archive's flag): 13 ran · 13 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 5 where Syntology's instrument failed) · 1 unverified (of 14 harvested samples) · 1 pointer-only (licence)
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Terrain Classification Enhanced with Uncertainty for Space Exploration Robots from Proprioceptive Data 3 Jul 2024 · 0 repositories · arXiv:2407.03241Syntology 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) · 1 unverified (of 7 harvested samples)
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Estimating Epistemic and Aleatoric Uncertainty with a Single Model 5 Feb 2024 · 1 repository · arXiv:2402.03478Syntology official (archive's flag): 2 ran · 3 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; 2 where Syntology's instrument failed) · 2 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation 26 Aug 2022 · 1 repository · arXiv:2208.12401Syntology official (archive's flag): 3 ran · 3 ran (of which 3 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) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result (of 4 harvested samples) · 4 pointer-only (licence)
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Variational Neural Networks 4 Jul 2022 · 3 repositories · arXiv:2207.01524Syntology official (archive's flag): 2 ran · 3 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; 2 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
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WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models 2 May 2022 · 1 repository · arXiv:2205.00865Syntology official (archive's flag): 3 ran · 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) · 8 unverified (of 11 harvested samples)
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Transformer Uncertainty Estimation with Hierarchical Stochastic Attention 27 Dec 2021 · 1 repository · arXiv:2112.13776Syntology official (archive's flag): 2 ran · 2 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; 0 where Syntology's instrument failed) · 3 unverified (of 5 harvested samples)
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Uncertainty-Aware Machine Translation Evaluation 13 Sep 2021 · 2 repositories · arXiv:2109.06352Syntology official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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Detecting Concept Drift With Neural Network Model Uncertainty 5 Jul 2021 · 1 repository · arXiv:2107.01873Syntology 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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Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts 7 Sep 2020 · 1 repository · arXiv:2009.02967Syntology official (archive's flag): 8 ran · 8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified (of 12 harvested samples) · 5 pointer-only (licence)
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On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation 22 Jan 2020 · 1 repository · arXiv:2001.08049Syntology 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) · 1 pointer-only (licence)
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Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference 30 Sep 2019 · 1 repository · arXiv:1909.13550Syntology 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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Probabilistic Object Detection: Definition and Evaluation 27 Nov 2018 · 1 repository · arXiv:1811.10800Syntology 7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 7 harvested samples)
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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning 6 Jun 2015 · 29 repositories · arXiv:1506.02142Syntology 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)