2021

Deep Neural Networks and Tabular Data: A Survey

Borisov, Vadim, Leemann, Tobias, Seßler, Kathrin et al.

Understand

Heterogeneous tabular data are the most commonly used form of data and are essential for numerous critical and computationally demanding applications.

On homogeneous data sets, deep neural networks have repeatedly shown excellent performance and have therefore been widely adopted.
However, their adaptation to tabular data for inference or data generation tasks remains challenging.
To facilitate further progress in the field, this work provides an overview of state-of-the-art deep learning methods for tabular data.

Built on

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