On Embeddings for Numerical Features in Tabular Deep Learning

Yury Gorishniy, Ivan Rubachev, Artem Babenko

Recently, Transformer-like deep architectures have shown strong performance on tabular data problems. Unlike traditional models, e.g., MLP, these architectures map scalar values of…