4 papers · 1 filter
Beyond IID: How General Are Tabular Foundation Models, Really?
Lennart Purucker, Andrej Tschalzev, Nick Erickson +7
Foundation models for predictive machine learning on tabular data have recently gained significant traction in academia and industry. Research communities across disciplines are in…
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Andrej Tschalzev, Nick Erickson, Yuyang Wang +4
Progress in tabular machine learning has largely focused on increasingly sophisticated model architectures. At the same time, feature engineering remains a critical yet underexplor…
TabArena: A Living Benchmark for Machine Learning on Tabular Data
Nick Erickson, Lennart Purucker, Andrej Tschalzev +4
With the growing popularity of deep learning and foundation models for tabular data, the need for standardized and reliable benchmarks is higher than ever. However, current benchma…
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications
David Salinas, Nick Erickson
We introduce TabRepo, a new dataset of tabular model evaluations and predictions. TabRepo contains the predictions and metrics of 1310 models evaluated on 200 classification and re…