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Code for the paper: Interpreting Deep Models through the Lens of Data

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License: MIT

Interpreting Deep Models through the Lens of Data

Code release for Interpreting Deep Models through the Lens of Data at ICJNN 2020

Paper:

https://arxiv.org/abs/2005.03442

https://doi.org/10.1109/IJCNN48605.2020.9207704

The used datasets are publically available:

Anomaly detection dataset: https://bit.ly/2UNk0Lo

FordB and Character Trajectories: http://www.timeseriesclassification.com/index.php

Use the main.py file to execute a selected procedure or the execute.sh file for a complete analysis. The .ipynb files provide additional methods to perform a post-hoc analysis using the trained models.

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