Tabular Regression

Tabular regression — predicting continuous values from structured data — powers everything from house-price estimation to demand forecasting and shares the same tree-vs-neural tension as classification. XGBoost and LightGBM remain brutally effective defaults, but recent work on differentiable trees and table-aware transformers (TabPFN, 2022) showed that meta-learned priors can beat tuned GBDTs on small datasets in seconds. The challenge is distribution shift: real-world regression targets drift over time, and most benchmarks (UCI, Kaggle) are static snapshots that hide this problem entirely.