2022
Anomaly Detection for Tabular Data with Internal Contrastive Learning
ICLR 2022poster
We consider the task of finding out-of-class samples in tabular data, where little can be assumed on the structure of the data. In order to capture the structure of the samples of the single training class, we learn mappings that maximize the mutual information between each sample and the part that…