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A pytorch lightning implementation of VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain

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VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain

Welcome to the PyTorch Lightning implementation of VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain (ICML'2020). This project is an unofficial implementation and was developed to mirror the methods described in the VIME paper as closely as possible.

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Install

pip install -r requirements.txt

Usage

See the example_*.ipynb

The official implementation generates static mask vectors, feature vectors, and corrupted samples during initialization of the dataset.

However, we generate them dynamically whenever call '__getitem__' of the dataset to avoid bias.

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A pytorch lightning implementation of VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain

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