Methods › General › Deep Tabular Learning › TabTransformer
TabTransformer
Introduced by Xin Huang et al. in TabTransformer: Tabular Data Modeling Using Contextual Embeddings
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
TabTransformer is a deep tabular data modeling architecture for supervised and semi-supervised learning. The TabTransformer is built upon self-attention based Transformers. The Transformer layers transform the embeddings of categorical features into robust contextual embeddings to achieve higher prediction accuracy.
As an overview, the architecture comprises a column embedding layer, a stack of N Transformer layers, and a multi-layer perceptron (MLP). The contextual embeddings (outputted by the Transformer layer) are concatenated along with continuous features which is inputted to an MLP. The loss function is then minimized to learn all the parameters in an end-to-end learning.
Papers archive 2025-07-28
9 shown of 9, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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A Robust PPO-optimized Tabular Transformer Framework for Intrusion Detection in Industrial IoT Systems 23 May 2025 · 1 repository · arXiv:2505.18234
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DeepOFormer: Deep Operator Learning with Domain-informed Features for Fatigue Life Prediction 28 Mar 2025 · 0 repositories · arXiv:2503.22475
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Application of Tabular Transformer Architectures for Operating System Fingerprinting 13 Feb 2025 · 1 repository · arXiv:2502.09084
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A Survey on Deep Tabular Learning 15 Oct 2024 · 0 repositories · arXiv:2410.12034
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Gradient Boosting Decision Trees on Medical Diagnosis over Tabular Data 25 Sep 2024 · 1 repository · arXiv:2410.03705
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Towards a Transformer-Based Pre-trained Model for IoT Traffic Classification 26 Jul 2024 · 1 repository · arXiv:2407.19051
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Deep Learning with Tabular Data: A Self-supervised Approach 26 Jan 2024 · 1 repository · arXiv:2401.15238
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The GatedTabTransformer. An enhanced deep learning architecture for tabular modeling 1 Jan 2022 · 2 repositories · arXiv:2201.00199
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TabTransformer: Tabular Data Modeling Using Contextual Embeddings 11 Dec 2020 · 12 repositories · arXiv:2012.06678Syntology ran 1 of 4 samples · 3 unverified · 4 pointer-only (licence)
Tasks archive 2025-07-28
19 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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