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interpretability-papers's Introduction

Interpretability Papers

This repository is for tracking papers on interpretable/explainable machine learning (primarily focusing on deep learning).

Papers are tracked as github issues (each issue should contain at least the title and a link to the paper, preferably also an abstract and bibtex citation information). Reviews/summaries of the paper should be entered in the issue commetns section.

A note about referencing:

If you find a newer reference for an article (e.g. a preprint on arXiv is published in a journal/conference proceedings), please update the bibtex entry in the relevant issue to refer to the latest article version. Probably best to check this yourself for any arXiv references before putting them in one of your own papers...

Useful site for Bibtex references from arXiv pages: https://arxiv2bibtex.org/

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