Erel Naor

Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings

Deep neural networks often under-perform on tabular data due to their sensitivity to irrelevant features and a spectral bias toward smooth, low-frequency functions. These limitations hinder their ability to capture the sharp, high-frequency signals that often define tabular structure, especially und…