ML Interpretability: Simple Isn't Easy

24 November 2022

Papers citing "ML Interpretability: Simple Isn't Easy"

5 / 5 papers shown

Title
Interpretable Machine Learning in Physics: A Review Sebastian Johann Wetzel Seungwoong Ha Raban Iten Miriam Klopotek Ziming Liu AI4CE 80 0 0 30 Mar 2025
MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification S. Goerttler Yucheng Wang Emadeldeen Eldele Min Wu F. He 38 0 0 06 Jan 2025
This Probably Looks Exactly Like That: An Invertible Prototypical Network Zachariah Carmichael Timothy Redgrave Daniel Gonzalez Cedre Walter J. Scheirer BDL 39 2 0 16 Jul 2024
Pixel-Grounded Prototypical Part Networks Zachariah Carmichael Suhas Lohit A. Cherian Michael Jeffrey Jones Walter J. Scheirer 38 11 0 25 Sep 2023
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,684 0 28 Feb 2017