A collection of research materials on explainable AI/ML
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Updated
Oct 29, 2024 - Markdown
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.
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A list of research papers of explainable machine learning.
Recourse Explanation Library in JAX
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.
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Python implementation of the work "The importance of Time in Causal Algorithmic Recourse"
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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