Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

2018 · PubMed · 1,477 citations · 0 from inside this corpus

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.

2 of 2 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

Paper	Year	Cited
Adam: A Method for Stochastic Optimization	2014	84,698
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach	2017	1,464

Links

DOI · Open access copy · OpenAlex record

Topics

Machine Learning and Data Classification	Computer Science
Anomaly Detection Techniques and Applications	Computer Science
Adversarial Robustness in Machine Learning	Computer Science

Is this record sound?

complete

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

supports2 author record(s) attached.
supports36 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 2026-09-04T03:58:58+00:00.

sha256 88a60cdbb94c6a13…