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The pytorch implementation of paper "Uncertainty-Aware Attention for Reliable Interpretation and Prediction" by Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee.

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Uncertainty-Aware-Pytorch-Implem

The pytorch implementation of paper "Uncertainty-Aware Attention for Reliable Interpretation and Prediction" by Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee. Based on its Tensorflow implementation from the original authors here

Requirements Python 3.7.x, Pytorch 1.1.x

Provided in dir dataset: Physionet in numpy format predicting mortatility risk Other dataset can be found here for Physionet for MIMIC-III dataset.

This implementation was able to achieve ~76% AUCROC on the provided evaluation dataset which is short of the ~78% claimed in the paper. The configuration follows exactly the configuration in the original implementation by the authors.

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The pytorch implementation of paper "Uncertainty-Aware Attention for Reliable Interpretation and Prediction" by Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee.

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