Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. We further analyze the viability of tabular self-supervised learning by introducing VIME [2], an established representation learning framework for tabular dat
