2 citations · 2 across the 1 of their papers we have counts for
3 papers
TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
Léo Grinsztajn, Klemens Flöge, Oscar Key +23
The first tabular foundation model, TabPFN, and its successor TabPFNv2 have impacted tabular AI substantially, with dozens of methods building on it and hundreds of applications ac…
Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data
David Holzmüller, Léo Grinsztajn, Ingo Steinwart
For classification and regression on tabular data, the dominance of gradient-boosted decision trees (GBDTs) has recently been challenged by often much slower deep learning methods…
CARTE: Pretraining and Transfer for Tabular Learning
Myung Jun Kim, Léo Grinsztajn, Gaël Varoquaux
Pretrained deep-learning models are the go-to solution for images or text. However, for tabular data the standard is still to train tree-based models. Indeed, transfer learning on…