TabPack

TabPack: Hyperparameter-ensemble MLP method for tabular deep learning with strong out-of-the-box performance

TabPack is a new efficient ensemble method for tabular deep learning that samples and trains many MLPs with different hyperparameters in parallel within a single run, selecting ensemble members on the fly. The approach eliminates the need for precise hyperparameter tuning by requiring only sampling ranges rather than exact values. On medium-to-large public datasets, default TabPack settings match extensively tuned prior methods while running faster than some baselines even on consumer hardware.