Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning
Publication
, Journal Article
Bastawrous, MV; Chen, Z; Ogren, A; Daraio, C; Rudin, C; Brinson, LC
Duke Scholars
Citation
APA
Chicago
ICMJE
MLA
NLM
Bastawrous, M. V., Chen, Z., Ogren, A., Daraio, C., Rudin, C., & Brinson, L. C. (n.d.). Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning.
Bastawrous, Mary V., Zhi Chen, Alexander Ogren, Chiara Daraio, Cynthia Rudin, and L Catherine Brinson. “Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning,” n.d.
Bastawrous MV, Chen Z, Ogren A, Daraio C, Rudin C, Brinson LC. Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning.
Bastawrous, Mary V., et al. Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning.
Bastawrous MV, Chen Z, Ogren A, Daraio C, Rudin C, Brinson LC. Phononic Materials with Effectively Scale-Separated Hierarchical Features Using Interpretable Machine Learning.