🔍 Universal Neural Network for Tabular Data

Yandex Research lab introduced the TabM architecture for working with tabular data. The development outperformed classical machine learning models.

🎯 What's special about TabM?

1️⃣ Versatility: On 46 datasets, the model ranked 1.7 on average (between first and second). The closest competitor ranked 2.9 (almost third).

2️⃣ Ease of use: Does not require deep fine-tuning for each new dataset, unlike specialized solutions.

3️⃣ Efficiency: Competes in quality with the best gradient boosting models (CatBoost, XGBoost).

💊 Where is it already used?

On the Kaggle platform, TabM was used to predict patient survival after bone marrow transplantation. The model analyzed data from similar cases and made predictions for new patients.

🔬 Scientific recognition

The work was presented at the ICLR conference and made publicly available on GitHub. Since 2019, Yandex Research researchers have published 8 papers on tabular data, accumulating over 1,900 citations.

👩‍💻 Data Flow

🚀 If you've already tested the architecture, share your impressions in the comments.