Who Cited It

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

2016 · arXiv (Cornell University) · 1,627 citations · 3 from inside this corpus

Dan Hendrycks, Kevin Gimpel

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.

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks (2016)A Baseline for Detecting Misc…On Calibration of Modern Neural Networks (2017)On Calibration of Modern Neur…Deep Learning for Anomaly Detection: A Review (2020)Deep Learning for Anomaly Det…Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and … (2021)Aleatoric and epistemic uncer…
3 of 3 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

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

What cites it, inside the corpus

PaperYearCited
On Calibration of Modern Neural Networks20171,741
Deep Learning for Anomaly Detection: A Review20201,731
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and …20211,596

Links

Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Anomaly Detection Techniques and ApplicationsComputer Science

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

  • supports2 author record(s) attached.
  • weakensNo references are recorded despite 1,627 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

sha256 7bc26169e93749d1…