Léo Grinsztajn

According to our database, Léo Grinsztajn authored at least 10 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

TabPFN-3: Technical Report.

Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Mihir Manium, Shi Bin Hoo, Magnus Bühler, Anurag Garg, Dominik Safaric, Jake Robertson, Benjamin Jäger, Simone Alessi, Adrian Hayler, Vladyslav Moroshan, Lennart Purucker, Philipp Singer, Alan Arazi, Julien Siems, Jan Hendrik Metzen, Georg Grab, Nick Erickson, Siyuan Guo, Eliott Kalfon, Simon Bing, David Salinas, Clara Cornu, Lilly Charlotte Wehrhahn, Diana Kriuchkova, Kursat Kaya, Lydia Sidhoum, Marie Salmon, Jerry Chen, Madelon Hulsebos, Yann LeCun, Samuel Müller, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter

CoRR, May, 2026

2025

TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models.

Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Benjamin Jäger, Dominik Safaric, Simone Alessi, Adrian Hayler, Mihir Manium, Rosen Yu, Felix Jablonski, Shi Bin Hoo, Anurag Garg, Jake Robertson, Magnus Bühler, Vladyslav Moroshan, Lennart Purucker, Clara Cornu, Lilly Charlotte Wehrhahn, Alessandro Bonetto, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter

CoRR, November, 2025

2024

Reconciling deep learning with tabular data. (Réconcilier l'apprentissage profond avec les données tabulaires).

Léo Grinsztajn

PhD thesis, 2024

Better by default: Strong pre-tuned MLPs and boosted trees on tabular data.

David Holzmüller, Léo Grinsztajn, Ingo Steinwart

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

CARTE: Pretraining and Transfer for Tabular Learning.

Myung Jun Kim, Léo Grinsztajn, Gaël Varoquaux

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Vectorizing string entries for data processing on tables: when are larger language models better?

Léo Grinsztajn, Edouard Oyallon, Myung Jun Kim, Gaël Varoquaux

CoRR, 2023

2022

Interpreting Neural Networks through the Polytope Lens.

Sid Black, Lee Sharkey, Léo Grinsztajn, Eric Winsor, Dan Braun, Jacob Merizian, Kip Parker, Carlos Ramón Guevara, Beren Millidge, Gabriel Alfour, Connor Leahy

CoRR, 2022

Why do tree-based models still outperform deep learning on tabular data?

Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux

CoRR, 2022

Why do tree-based models still outperform deep learning on typical tabular data?

Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference.

Achille Thin, Nikita Kotelevskii, Jean-Stanislas Denain, Léo Grinsztajn, Alain Durmus, Maxim Panov, Eric Moulines

CoRR, 2020