| Revisiting deep learning models for tabular data Y Gorishniy, I Rubachev, V Khrulkov, A Babenko Advances in Neural Information Processing Systems 34, 18932-18943, 2021 | 887 | 2021 |
| On embeddings for numerical features in tabular deep learning Y Gorishniy, I Rubachev, A Babenko Advances in Neural Information Processing Systems 35, 24991-25004, 2022 | 192 | 2022 |
| TabR: Tabular Deep Learning Meets Nearest Neighbors Y Gorishniy, I Rubachev, N Kartashev, D Shlenskii, A Kotelnikov, ... The Twelfth International Conference on Learning Representations, 2024 | 55* | 2024 |
| Revisiting Pretraining Objectives for Tabular Deep Learning I Rubachev, A Alekberov, Y Gorishniy, A Babenko arXiv preprint arXiv:2207.03208, 2022 | 54 | 2022 |
| TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling Y Gorishniy, A Kotelnikov, A Babenko arXiv preprint arXiv:2410.24210, 2024 | 7 | 2024 |
| Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks I Rubachev, N Kartashev, Y Gorishniy, A Babenko The Thirteenth International Conference on Learning Representations, 0 | 7* | |
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