Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning

6 May 2021

Papers citing "Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning"

3 / 3 papers shown

Title
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean Anton Thielmann René-Marcel Kruse Thomas Kneib Benjamin Säfken 32 12 0 27 Jan 2023
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Zou 145 188 0 31 May 2022
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 655 0 20 Mar 2021