Research on Tabular Deep Learning (Python package & papers)

Research on Tabular Deep Learning

For paper implementations, see the section "Papers and projects".

rtdl is a PyTorch-based package providing a user-friendly API for the main models and concepts from our papers. See the documentation.

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Papers and projects

Name Location Comment
On Embeddings for Numerical Features in Tabular Deep Learning link arXiv 2022
Revisiting Deep Learning Models for Tabular Data link NeurIPS 2021
rtdl link Python package
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Comments
  • Is it possible to provide a scikit-learn interface?

    Is it possible to provide a scikit-learn interface?

    This project is interesting and I want to use it as the baseline algorithm for my paper. However, it seems that I need to take several steps in order to make a prediction. Consequently, is it possible to provide a scikit-learn interface for making a convenient comparison between different algorithms?

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    This PR aims to add basic Weights and Biases Metric Logging by appending to the existing codebase with minimal changes while supporting Checkpoint uploads as Weights and Biases Artifacts.

    Wherever needed, I have used the existing Weights and Biases integrations viz. LightGBM and XGBoost.

    I have validated the performance of all the proposed runs by running 150+ runs, which can be viewed on this project page and in detail in an accompanying blog post.

  • A scikit-learn interface for RTDL package.

    A scikit-learn interface for RTDL package.

    Hello! I have written a scikit-learn interface for the RTDL package (https://github.com/hengzhe-zhang/scikit-rtdl). I rely on the skorch to avoid coding errors, and set the default parameters based on the parameters presented in your paper. Hoping you will like it!

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