Introducing TabH2O

This post announces tabH2O, a new foundation model for tabular data. It details the model's dual-head architecture for classification and regression, and highlights stability improvements in its single-stage pretraining, including bounded scalable softmax, inter-stage normalization, learnable residual scaling, and logit soft-capping. It also mentions noise-aware pretraining for robustness to irrelevant features.