Who Cited It

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

2018 · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2,873 citations · 5 from inside this corpus

Takeru Miyato, Shin‐ichi Maeda, Masanori Koyama, Shin Ishii

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised … (2018)Virtual Adversarial Training:…Adam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics… (2015)[No title in the source recor…Dropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2015)Batch Normalization: Accelera…Explaining and Harnessing Adversarial Examples (2014)Explaining and Harnessing Adv…Intriguing properties of neural networks (2013)Intriguing properties of neur…Deep Sparse Rectifier Neural Networks (2011)Deep Sparse Rectifier Neural …Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning (2015)Dropout as a Bayesian Approxi…Pattern recognition and machine learning (2007)Pattern recognition and machi…Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning (2015)Dropout as a Bayesian Approxi…Static Analysis of Shape in TensorFlow Programs (2016)Static Analysis of Shape in T…Learning from Labeled and Unlabeled Data with Label Propagation (2002)Learning from Labeled and Unl…Bootstrap your own latent: A new approach to self-supervised Learning (2020)Bootstrap your own latent: A …A survey on semi-supervised learning (2019)A survey on semi-supervised l…FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence (2020)FixMatch: Simplifying Semi-Su…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Unsupervised Data Augmentation for Consistency Training (2019)Unsupervised Data Augmentatio…
17 of 17 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Adam: A Method for Stochastic Optimization201484,698
[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…201550,396
Dropout: a simple way to prevent neural networks from overfitting201434,236
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…201524,404
Explaining and Harnessing Adversarial Examples20148,146
Intriguing properties of neural networks20135,739
Deep Sparse Rectifier Neural Networks20115,428
Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning20154,187
Pattern recognition and machine learning20072,691
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning20152,672
Static Analysis of Shape in TensorFlow Programs20161,686
Learning from Labeled and Unlabeled Data with Label Propagation20021,570

What cites it, inside the corpus

PaperYearCited
Bootstrap your own latent: A new approach to self-supervised Learning20203,447
A survey on semi-supervised learning20192,636
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence20202,271
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
Unsupervised Data Augmentation for Consistency Training20191,624

Links

DOI · OpenAlex record

Topics

Adversarial Robustness in Machine LearningComputer Science
Anomaly Detection Techniques and ApplicationsComputer Science
Advanced Neural Network ApplicationsComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports4 author record(s) attached.
  • supports92 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:48+00:00.

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