Sep 13, 2024 · In this study, we propose a method based on the TabKANet architecture, which utilizes the Kolmogorov-Arnold network to encode numerical features and merge them ...
Sep 13, 2024 · In this study, we propose a method based on the TabKANet architecture, which utilizes the Kolmogorov-Arnold network to encode numerical features ...
KAN model replaces MLP with Kolmogorov-Arnold Network to achieve table data learning. TabTransformer adapts the Transformer architecture for the categorical ...
In this study, we propose the TabKANet model for tabular data modeling, which targets the bottlenecks in learning from numerical content. We constructed a ...
In this study, we propose a method based on the TabKANet architecture, which utilizes the Kolmogorov-Arnold network to encode numerical features and merge them ...
TabKANet: Tabular Data Modelling with Kolmogorov-Arnold Network ...
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Sep 15, 2024 · TL;DR: TabKANet is a new tabular data modeling method that combines Kolmogorov-Arnold Networks and Transformers, showing improved performance ...
Oct 2, 2024 · TabKANet is a new deep learning model for tabular data modeling that combines the Kolmogorov-Arnold Network (KAN) and Transformer architectures.
Sep 14, 2024 · TabKANet, Use Kolmogorov Arnold network and Transformer to unify tabular data modeling. - tsinghuamedgao20/TabKANet.
Sep 16, 2024 · TabKANet: Tabular Data Modelling with Kolmogorov-Arnold Network... Tabular data is the most common type of data in real-life scenarios. In this ...
We introduce TabKANet, a novel model that leverages a KAN-based Numerical Embedding Module and Transformer to overcome neural networks' limitations in tabular ...