Methods › Computer Vision › Image Data Augmentation › Mixup › Papers, page 7

Mixup

Papers archive 2025-07-28

archive papers tagged: 651 · with a code link: 308 · where Syntology ran a sample: 89 (74 with a run with no instrument failure, 15 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (89 of 651 tagged: 74 with a run with no instrument failure, 15 where every run was a failure of Syntology's instrument)

Page 7 of 7: papers 601 to 651 of 651, newest first by the archive's date (ties by slug), in archive order.

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.

• Exploring Long Tail Visual Relationship Recognition with Large Vocabulary
  25 Mar 2020 · 3 repositories · arXiv:2004.00436
  Syntology official (archive's flag): 2 ran · 5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples)
• Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation
  23 Mar 2020 · 0 repositories · arXiv:2003.10042
• On Calibration of Mixup Training for Deep Neural Networks
  22 Mar 2020 · 1 repository · arXiv:2003.09946
• ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging
  20 Mar 2020 · 1 repository · arXiv:2003.09439
• On the benefits of defining vicinal distributions in latent space
  14 Mar 2020 · 0 repositories · arXiv:2003.06566
• Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
  5 Mar 2020 · 2 repositories · arXiv:2003.02484
• FMix: Enhancing Mixed Sample Data Augmentation
  27 Feb 2020 · 5 repositories · arXiv:2002.12047
  Syntology official (archive's flag): 5 ran · 8 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; 7 where Syntology's instrument failed) · 0 unverified (of 8 harvested samples) · 3 pointer-only (licence)
• Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration
  10 Feb 2020 · 0 repositories · arXiv:2002.03875
• batchboost: regularization for stabilizing training with resistance to underfitting & overfitting
  21 Jan 2020 · 1 repository · arXiv:2001.07627
• Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network
  17 Jan 2020 · 1 repository · arXiv:2001.06268
  Syntology 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)
• Improve Unsupervised Domain Adaptation with Mixup Training
  3 Jan 2020 · 1 repository · arXiv:2001.00677
• Big Transfer (BiT): General Visual Representation Learning
  24 Dec 2019 · 9 repositories · arXiv:1912.11370
  Syntology community repositories only · 9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified (of 10 harvested samples)
• On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration
  16 Dec 2019 · 0 repositories · arXiv:1912.07458
• Adversarial Domain Adaptation with Domain Mixup
  4 Dec 2019 · 1 repository · arXiv:1912.01805
• E-Stitchup: Data Augmentation for Pre-Trained Embeddings
  28 Nov 2019 · 0 repositories · arXiv:1912.00772
• Learning Spatial Fusion for Single-Shot Object Detection
  21 Nov 2019 · 1 repository · arXiv:1911.09516
• Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy
  21 Nov 2019 · 0 repositories · arXiv:1911.09307
• Model-agnostic Approaches to Handling Noisy Labels When Training Sound Event Classifiers
  26 Oct 2019 · 1 repository · arXiv:1910.12004
• Urban Sound Tagging using Convolutional Neural Networks
  27 Sep 2019 · 1 repository · arXiv:1909.12699
• Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
  25 Sep 2019 · 1 repository · arXiv:1909.11515
  Syntology official (archive's flag): 2 ran · 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 3 harvested samples)
• Cross-Corpus Data Augmentation for Acoustic Addressee Detection
  1 Sep 2019 · 0 repositories
• Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography
  27 Aug 2019 · 0 repositories · arXiv:1908.09993
• MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning
  27 Aug 2019 · 0 repositories · arXiv:1908.10059
• Mish: A Self Regularized Non-Monotonic Activation Function
  23 Aug 2019 · 9 repositories · arXiv:1908.08681
  Syntology 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)
• Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation
  12 Aug 2019 · 1 repository · arXiv:1908.04126
• Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
  8 Aug 2019 · 4 repositories · arXiv:1908.02983
  Syntology 14 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; 2 where Syntology's instrument failed) · 6 unverified (of 20 harvested samples) · 3 pointer-only (licence)
• Efficient Method for Categorize Animals in the Wild
  30 Jul 2019 · 1 repository · arXiv:1907.13037
• Charting the Right Manifold: Manifold Mixup for Few-shot Learning
  28 Jul 2019 · 8 repositories · arXiv:1907.12087
• Mixup of Feature Maps in a Hidden Layer for Training of Convolutional Neural Network
  24 Jun 2019 · 0 repositories · arXiv:1906.09739
• Data Interpolating Prediction: Alternative Interpretation of Mixup
  20 Jun 2019 · 0 repositories · arXiv:1906.08412
• MixUp as Directional Adversarial Training
  17 Jun 2019 · 0 repositories · arXiv:1906.06875
• Suppressing Model Overfitting for Image Super-Resolution Networks
  11 Jun 2019 · 0 repositories · arXiv:1906.04809
• Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples
  1 Jun 2019 · 0 repositories
• On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
  27 May 2019 · 2 repositories · arXiv:1905.11001
• Augmenting Data with Mixup for Sentence Classification: An Empirical Study
  22 May 2019 · 3 repositories · arXiv:1905.08941
  Syntology 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) · 0 unverified (of 2 harvested samples)
• Multi-class Novelty Detection Using Mix-up Technique
  11 May 2019 · 0 repositories · arXiv:1905.04523
• Virtual Mixup Training for Unsupervised Domain Adaptation
  10 May 2019 · 4 repositories · arXiv:1905.04215
• Manifold Mixup: Learning Better Representations by Interpolating Hidden States
  1 May 2019 · 1 repository
• Unsupervised Label Noise Modeling and Loss Correction
  25 Apr 2019 · 2 repositories · arXiv:1904.11238
  Syntology 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
• Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
  10 Apr 2019 · 28 repositories · arXiv:1904.05049
  Syntology community repositories only · 24 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 0 violated, 10 with no contract checked; 13 where Syntology's instrument failed) · 10 unverified (of 34 harvested samples) · 9 pointer-only (licence)
• CondConv: Conditionally Parameterized Convolutions for Efficient Inference
  10 Apr 2019 · 9 repositories · arXiv:1904.04971
• Blur Removal via Blurred-Noisy Image Pair
  26 Mar 2019 · 0 repositories · arXiv:1903.10667
• Manifold Mixup improves text recognition with CTC loss
  11 Mar 2019 · 1 repository · arXiv:1903.04246
• Bag of Tricks for Image Classification with Convolutional Neural Networks
  4 Dec 2018 · 28 repositories · arXiv:1812.01187
  Syntology 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)
• Generalization Bounds for Vicinal Risk Minimization Principle
  11 Nov 2018 · 0 repositories · arXiv:1811.04351
• Label Denoising with Large Ensembles of Heterogeneous Neural Networks
  12 Sep 2018 · 0 repositories · arXiv:1809.04403
• MixUp as Locally Linear Out-Of-Manifold Regularization
  7 Sep 2018 · 2 repositories · arXiv:1809.02499
  Syntology 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 2 harvested samples) · 2 pointer-only (licence)
• Manifold Mixup: Better Representations by Interpolating Hidden States
  13 Jun 2018 · 12 repositories · arXiv:1806.05236
  Syntology official: no sample here; runs from other or unrecorded repositories · 7 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; 2 where Syntology's instrument failed) · 4 unverified (of 11 harvested samples) · 5 pointer-only (licence)
• Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network
  18 May 2018 · 0 repositories · arXiv:1805.07319
• Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples
  26 Feb 2018 · 0 repositories · arXiv:1802.09502
• mixup: Beyond Empirical Risk Minimization
  25 Oct 2017 · 71 repositories · arXiv:1710.09412
  Syntology community repositories only · 36 ran (of which 5 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 20 where Syntology's instrument failed) · 11 unverified (of 47 harvested samples) · 15 pointer-only (licence)