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Detecting Adversarial Examples Via Neural Fingerprinting

Machine Learning Project - ICLR Reproducibility Challenge

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Development

Platforms used

During the development phase we used different platforms to execute our code. We started testing out on our personal computers, then we moved to Google Cloud Platform and finally to Google Colab Notebook. Google Colab Notebook turned out to be the best since it provides a free GPU and can be share among multiple users.

Research of the papers

There are thousands of papers submitted to the ICLR conference. Before deciding which paper to review, we spent some times looking for a convincing paper. Our approach has been first to download all papers locally, then order by number of comments and finally manually find an available paper that appeared interesting.

  • /find-papers folder contains code to download and parse all papers submitted to the ICLR conference at openreview.net, order by number of comments

Code

An executed version of the Jupyter Notebook is accessible on google colab platform at the following address: go.epfl.ch/neural-fingerprinting

The same version is also available locally at the following path: ./run.ipynb

Paper

Our research is coupled with a paper available here: report.pdf

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