A collection of research materials on explainable AI/ML
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Updated
May 1, 2024
A collection of research materials on explainable AI/ML
This is the official repository of the paper "RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model".
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CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Python implementation of the work "The importance of Time in Causal Algorithmic Recourse"
Recourse Explanation Library in JAX
This project Implements the paper “Robustness implies Fairness in Casual Algorithmic Recourse” using the R language.
This is the official repository of the paper "CounterNet: End-to-End Training of Counterfactual Aware Predictions".
A list of research papers of explainable machine learning.
A collection of algorithms of counterfactual explanations.
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Code associated with "Recourse For Humans", presented at the Participatory Approaches to Machine Learning workshop at ICML 2020.
Add a description, image, and links to the recourse topic page so that developers can more easily learn about it.
To associate your repository with the recourse topic, visit your repo's landing page and select "manage topics."