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A collection of research materials on explainable AI/ML
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
A collection of algorithms of counterfactual explanations.
A list of research papers of explainable machine learning.
This is the official repository of the paper "CounterNet: End-to-End Training of Counterfactual Aware Predictions".
This project Implements the paper “Robustness implies Fairness in Casual Algorithmic Recourse” using the R language.
Code associated with "Recourse For Humans", presented at the Participatory Approaches to Machine Learning workshop at ICML 2020.
This is the official repository of the paper "RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model".
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