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How to See Hidden Patterns in Metamaterials with Interpretable Machine
  Learning
v1v2v3v4 (latest)

How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning

Extreme Mechanics Letters (Extreme Mech. Lett.), 2021
10 November 2021
Zhi Chen
Alexander C. Ogren
Chiara Daraio
L. C. Brinson
Cynthia Rudin
ArXiv (abs)PDFHTMLGithub

Papers citing "How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning"

7 / 7 papers shown
Populating cellular metamaterials on the extrema of attainable elasticity through neuroevolution
Populating cellular metamaterials on the extrema of attainable elasticity through neuroevolutionComputer Methods in Applied Mechanics and Engineering (CMAME), 2024
Maohua Yan
Ruicheng Wang
Ke Liu
581
6
0
15 Dec 2024
Phononic materials with effectively scale-separated hierarchical
  features using interpretable machine learning
Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning
Mary V. Bastawrous
Zhi Chen
Alexander C. Ogren
Chiara Daraio
Cynthia Rudin
L. C. Brinson
114
1
0
15 Aug 2024
Generative Inverse Design of Metamaterials with Functional Responses by
  Interpretable Learning
Generative Inverse Design of Metamaterials with Functional Responses by Interpretable LearningAdvanced Intelligent Systems (Adv. Intell. Syst.), 2023
Wei Chen
Rachel Sun
Doksoo Lee
Carlos M. Portela
Wei Chen
AI4CE
514
18
0
08 Dec 2023
Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with
  Stochastic Geometric Defects and Material Properties
Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties
Han Zhang
R. K. Mahabadi
Cynthia Rudin
Johann Guilleminot
L. C. Brinson
99
0
0
19 Oct 2023
Data-Driven Design for Metamaterials and Multiscale Systems: A Review
Data-Driven Design for Metamaterials and Multiscale Systems: A ReviewAdvances in Materials (AM), 2023
Doksoo Lee
Wei Chen
Liwei Wang
Yu-Chin Chan
Wei Chen
AI4CE
255
193
0
01 Jul 2023
Harnessing Interpretable Machine Learning for Holistic Inverse Design of
  Origami
Harnessing Interpretable Machine Learning for Holistic Inverse Design of OrigamiScientific Reports (Sci Rep), 2022
Yi Zhu
E. Filipov
AI4CE
167
8
0
12 Apr 2022
Interpretable Machine Learning: Fundamental Principles and 10 Grand
  Challenges
Interpretable Machine Learning: Fundamental Principles and 10 Grand ChallengesStatistics Survey (Stat. Surv.), 2021
Cynthia Rudin
Chaofan Chen
Zhi Chen
Haiyang Huang
Lesia Semenova
Chudi Zhong
FaMLAI4CELRM
530
913
0
20 Mar 2021
1
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