TL;DR探讨深度神经网络架构与训练机制与其相应的选择性预测和不确定性估计性能的关系,并在 484 个预训练的深度 Imagenet 分类器中进行了全面的选择性预测和不确定性估计性能研究,发现 ViT 架构在不确定性估计性能方面表现最优。
Abstract
Due to the comprehensive nature of this paper, it has been updated and split
into two separate papers: "A Framework For Benchmarking
Class-out-of-distribution Detection And Its Application To ImageNet" and "What
Can We Learn From The Selective Prediction And uncertainty estimation
Perf