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cs.LG2021
How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning
Zhi Chen, Alexander Ogren, Chiara Daraio +2
Machine learning models can assist with metamaterials design by approximating computationally expensive simulators or solving inverse design problems. However, past work has usuall…
cs.LG2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges
Cynthia Rudin, Chaofan Chen, Zhi Chen +3
Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting. In this work, we provide fundamental principles for interpretable ML, and dispel…