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Corbière et al., 2019 - Google Patents

Addressing failure prediction by learning model confidence

Corbière et al., 2019

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Document ID
2867131902793640249
Author
Corbière C
Thome N
Bar-Hen A
Cord M
Pérez P
Publication year
Publication venue
Advances in neural information processing systems

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Snippet

Assessing reliably the confidence of a deep neural net and predicting its failures is of primary importance for the practical deployment of these models. In this paper, we propose a new target criterion for model confidence, corresponding to the True Class Probability (TCP) …
Continue reading at proceedings.neurips.cc (PDF) (other versions)

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