Who Cited It

Towards Deep Learning Models Resistant to Adversarial Attacks

2017 · arXiv (Cornell University) · 1,536 citations · 3 from inside this corpus

Aleksander Mądry low, Aleksandar Makelov low, Ludwig Schmidt low, Dimitris Tsipras low, Adrian Vladu

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.

Towards Deep Learning Models Resistant to Adversarial Attacks (2017)Towards Deep Learning Models …DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks (2016)DeepFool: A Simple and Accura…A unified architecture for natural language processing (2008)A unified architecture for na…Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks (2018)Feature Squeezing: Detecting …Adversarial Examples Are Not Easily Detected (2017)Adversarial Examples Are Not …Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversaria… (2016)Transferability in Machine Le…Advances and Open Problems in Federated Learning (2020)Advances and Open Problems in…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…ZOO (2017)ZOO
8 of 8 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.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks20165,392
A unified architecture for natural language processing20085,207
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks20181,882
Adversarial Examples Are Not Easily Detected20171,428
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversaria…20161,416

What cites it, inside the corpus

PaperYearCited
Advances and Open Problems in Federated Learning20205,383
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
ZOO20171,779

Links

DOI · Open access copy · OpenAlex record

Topics

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

Is this record sound?

complete

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

  • supports5 author record(s) attached.
  • supports30 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 2026-09-04T03:58:57+00:00.

sha256 b3024609427ad450…