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Data Science Principles for Interpretable and Explainable AI

Data Science Principles for Interpretable and Explainable AI

17 May 2024
Kris Sankaran
    FaML
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Papers citing "Data Science Principles for Interpretable and Explainable AI"

3 / 3 papers shown
Title
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
Fabian Fumagalli
Maximilian Muschalik
Patrick Kolpaczki
Eyke Hüllermeier
Barbara Hammer
27
27
0
02 Mar 2023
Exploring the Whole Rashomon Set of Sparse Decision Trees
Exploring the Whole Rashomon Set of Sparse Decision Trees
Rui Xin
Chudi Zhong
Zhi Chen
Takuya Takagi
Margo Seltzer
Cynthia Rudin
25
53
0
16 Sep 2022
Post-hoc Concept Bottleneck Models
Post-hoc Concept Bottleneck Models
Mert Yuksekgonul
Maggie Wang
James Y. Zou
133
182
0
31 May 2022
1