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Our paper, a recent NeurIPS publication,

  1. Provides a good survey of fairness algorithms in the deep learning space
  2. Codes and documentation for all the available fairness metrics
  3. We perform the most extensive analysis of modern deep fairness algorithms on how their bias detection and mitigation capabilities.
  4. Provides a novel dataset and has a codebase with all fairness models in one location
  5. Explains the social impact of biases in discussion, conclusion, supplementary material sections of the paper

Hence, I added our paper to all relevant sections in the README.

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