Who Cited It

Explaining and Harnessing Adversarial Examples

2014 · arXiv (Cornell University) · 8,146 citations · 18 from inside this corpus

Ian Goodfellow, Jonathon Shlens, Christian Szegedy

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.

Explaining and Harnessing Adversarial Examples (2014)Explaining and Harnessing Adv…Long Short-Term Memory (1997)Long Short-Term MemoryDropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Multilayer feedforward networks are universal approximators (1989)Multilayer feedforward networ…Intriguing properties of neural networks (2013)Intriguing properties of neur…Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe… (2019)Explainable Artificial Intell…DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks (2016)DeepFool: A Simple and Accura…The Limitations of Deep Learning in Adversarial Settings (2016)The Limitations of Deep Learn…Boosting Adversarial Attacks with Momentum (2018)Boosting Adversarial Attacks …Explainable AI: A Review of Machine Learning Interpretability Methods (2020)Explainable AI: A Review of M…Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised … (2018)Virtual Adversarial Training:…Universal Adversarial Perturbations (2017)Universal Adversarial Perturb…A survey on semi-supervised learning (2019)A survey on semi-supervised l…Robust Physical-World Attacks on Deep Learning Visual Classification (2018)Robust Physical-World Attacks…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks (2018)Feature Squeezing: Detecting …Adversarial Examples in the Physical World (2018)Adversarial Examples in the P…Adversarial Examples: Attacks and Defenses for Deep Learning (2019)Adversarial Examples: Attacks…ZOO (2017)ZOOAccessorize to a Crime (2016)Accessorize to a CrimeDeep Learning--based Text Classification (2021)Deep Learning--based Text Cla…Adversarial Examples Are Not Easily Detected (2017)Adversarial Examples Are Not …Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications (2021)Explaining Deep Neural Networ…
22 of 22 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
Long Short-Term Memory1997101,359
Dropout: a simple way to prevent neural networks from overfitting201434,236
Multilayer feedforward networks are universal approximators19899,357
Intriguing properties of neural networks20135,739

What cites it, inside the corpus

PaperYearCited
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…20199,796
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks20165,392
The Limitations of Deep Learning in Adversarial Settings20163,980
Boosting Adversarial Attacks with Momentum20183,040
Explainable AI: A Review of Machine Learning Interpretability Methods20202,907
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …20182,873
Universal Adversarial Perturbations20172,744
A survey on semi-supervised learning20192,636
Robust Physical-World Attacks on Deep Learning Visual Classification20182,154
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks20181,882
Adversarial Examples in the Physical World20181,842
Adversarial Examples: Attacks and Defenses for Deep Learning20191,786
ZOO20171,779
Accessorize to a Crime20161,596
Deep Learning--based Text Classification20211,525
Adversarial Examples Are Not Easily Detected20171,428
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications20211,424

Links

DOI · Open access copy · OpenAlex record

Topics

Adversarial Robustness in Machine LearningComputer Science
Explainable Artificial Intelligence (XAI)Computer Science
Anomaly Detection Techniques and ApplicationsComputer Science

Is this record sound?

complete

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

  • supports3 author record(s) attached.
  • supports14 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:43+00:00.

sha256 5cad55ac5d4d41e1…