Brent Griffin

Class-wise Autoencoders Measure Classification Difficulty And Detect Label Mistakes

2024 · arXiv (Cornell University)

We introduce a new framework for analyzing classification datasets based on the ratios of reconstruction errors between autoencoders trained on individual classes. This analysis framework enables efficient characterization of datasets on the sample, class, and …