1-20 of 46 Search Results for

*

Save search
Follow your search
Access your saved searches in your account
Close Modal
Sort by
Journal Articles

Accelerated and interpretable prediction of local properties in composites

Shengtong Zhang, Satyajit Mojumder, Wing Kam Liu, Wei Chen, Daniel W. Apley
Journal: APL Machine Learning
APL Mach. Learn. 1, 036112 (2023)
https://doi.org/10.1063/5.0156517
Published: September 2023
View article titled, Accelerated and interpretable prediction of local properties in composites
Open the PDF for Accelerated and interpretable prediction of local properties in composites in another window
Journal Articles

Experimental realization of a quantum classification: Bell state measurement via machine learning

Qing-Yuan Wu, Zhe Meng, Xiao-Xiao Chen, Jian Li, Jia-Zhi Yang, An-Ning Zhang
Journal: APL Machine Learning
APL Mach. Learn. 1, 036111 (2023)
https://doi.org/10.1063/5.0149414
Published: September 2023
View article titled, Experimental realization of a quantum classification: Bell state measurement via machine learning
Open the PDF for Experimental realization of a quantum classification: Bell state measurement via machine learning in another window
Journal Articles

KoopmanLab: Machine learning for solving complex physics equations

Wei Xiong, Muyuan Ma, Xiaomeng Huang, Ziyang Zhang, Pei Sun, Yang Tian
Journal: APL Machine Learning
APL Mach. Learn. 1, 036110 (2023)
https://doi.org/10.1063/5.0157763
Published: September 2023
View article titled, KoopmanLab: Machine learning for solving complex physics equations
Open the PDF for KoopmanLab: Machine learning for solving complex physics equations in another window
Journal Articles

Flexible optoelectronic synaptic transistors for neuromorphic visual systems

Xiao Liu, Dongke Li, Yue Wang, Deren Yang, Xiaodong Pi
Journal: APL Machine Learning
APL Mach. Learn. 1, 031501 (2023)
https://doi.org/10.1063/5.0163926
Published: August 2023
View article titled, Flexible optoelectronic synaptic transistors for neuromorphic visual systems
Open the PDF for Flexible optoelectronic synaptic transistors for neuromorphic visual systems in another window
Journal Articles

Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses

Nathan Leroux, Danijela Marković, Dédalo Sanz-Hernández, Juan Trastoy, Paolo Bortolotti, Alejandro Schulman, Luana Benetti, Alex Jenkins, Ricardo Ferreira, Julie Grollier, Frank Alice Mizrahi
Journal: APL Machine Learning
APL Mach. Learn. 1, 036109 (2023)
https://doi.org/10.1063/5.0155447
Published: August 2023
View article titled, Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses
Open the PDF for Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses in another window
Includes: Supplementary data
Journal Articles

Deep ensemble inverse model for image-based estimation of solar cell parameters

M. Battaglia, E. Comi, T. Stadelmann, R. Hiestand, B. Ruhstaller, E. Knapp
Journal: APL Machine Learning
APL Mach. Learn. 1, 036108 (2023)
https://doi.org/10.1063/5.0139707
Published: July 2023
View article titled, Deep ensemble inverse model for image-based estimation of solar cell parameters
Open the PDF for Deep ensemble inverse model for image-based estimation of solar cell parameters in another window
Journal Articles

Improved prediction for failure time of multilayer ceramic capacitors (MLCCs): A physics-based machine learning approach

Pedram Yousefian, Alireza Sepehrinezhad, Adri C. T. van Duin, Clive A. Randall
Journal: APL Machine Learning
APL Mach. Learn. 1, 036107 (2023)
https://doi.org/10.1063/5.0158360
Published: July 2023
View article titled, Improved prediction for failure time of multilayer ceramic capacitors (MLCCs): A physics-based machine learning approach
Open the PDF for Improved prediction for failure time of multilayer ceramic capacitors (MLCCs): A physics-based machine learning approach in another window
Journal Articles

3D CNN and grad-CAM based visualization for predicting generation of dislocation clusters in multicrystalline silicon

Kyoka Hara, Takuto Kojima, Kentaro Kutsukake, Hiroaki Kudo, Noritaka Usami
Journal: APL Machine Learning
APL Mach. Learn. 1, 036106 (2023)
https://doi.org/10.1063/5.0156044
Published: July 2023
View article titled, 3D CNN and grad-CAM based visualization for predicting generation of dislocation clusters in multicrystalline silicon
Open the PDF for 3D CNN and grad-CAM based visualization for predicting generation of dislocation clusters in multicrystalline silicon in another window
Journal Articles

Scalable wavelength-multiplexing photonic reservoir computing

Rui-Qian Li, Yi-Wei Shen, Bao-De Lin, Jingyi Yu, Xuming He, Cheng Wang
Journal: APL Machine Learning
APL Mach. Learn. 1, 036105 (2023)
https://doi.org/10.1063/5.0158939
Published: July 2023
View article titled, Scalable wavelength-multiplexing photonic reservoir computing
Open the PDF for Scalable wavelength-multiplexing photonic reservoir computing in another window
Includes: Supplementary data
Journal Articles

Resistance transient dynamics in switchable perovskite memristors

Juan Bisquert, Agustín Bou, Antonio Guerrero, Enrique Hernández-Balaguera
Journal: APL Machine Learning
APL Mach. Learn. 1, 036101 (2023)
https://doi.org/10.1063/5.0153289
Published: July 2023
View article titled, Resistance transient dynamics in switchable perovskite memristors
Open the PDF for Resistance transient dynamics in switchable perovskite memristors in another window
Journal Articles

Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks

F. Aguirre, E. Piros, N. Kaiser, T. Vogel, S. Petzold, J. Gehrunger, T. Oster, K. Hofmann, C. Hochberger, J. Suñé, L. Alff, E. Miranda
Journal: APL Machine Learning
APL Mach. Learn. 1, 036104 (2023)
https://doi.org/10.1063/5.0143926
Published: July 2023
View article titled, Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks
Open the PDF for Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks in another window
Journal Articles

Machine learning guided optimal composition selection of niobium alloys for high temperature applications

Trupti Mohanty, K. S. Ravi Chandran, Taylor D. Sparks
Journal: APL Machine Learning
APL Mach. Learn. 1, 036102 (2023)
https://doi.org/10.1063/5.0129528
Published: July 2023
View article titled, Machine learning guided optimal composition selection of niobium alloys for high temperature applications
Open the PDF for Machine learning guided optimal composition selection of niobium alloys for high temperature applications in another window
Includes: Supplementary data
Journal Articles

Automatic graph representation algorithm for heterogeneous catalysis

Zachary Gariepy, ZhiWen Chen, Isaac Tamblyn, Chandra Veer Singh, Conrard Giresse Tetsassi Feugmo
Journal: APL Machine Learning
APL Mach. Learn. 1, 036103 (2023)
https://doi.org/10.1063/5.0140487
Published: July 2023
View article titled, Automatic graph representation algorithm for heterogeneous catalysis
Open the PDF for Automatic graph representation algorithm for heterogeneous catalysis in another window
Includes: Supplementary data
Journal Articles

Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation

Adam N. McCaughan, Bakhrom G. Oripov, Natesh Ganesh, Sae Woo Nam, Andrew Dienstfrey, Sonia M. Buckley
Journal: APL Machine Learning
APL Mach. Learn. 1, 026118 (2023)
https://doi.org/10.1063/5.0157645
Published: June 2023
View article titled, Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation
Open the PDF for Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation in another window
Journal Articles

Brains and bytes: Trends in neuromorphic technology

Adnan Mehonic, Jason Eshraghian
Journal: APL Machine Learning
APL Mach. Learn. 1, 020401 (2023)
https://doi.org/10.1063/5.0162712
Published: June 2023
View article titled, Brains and bytes: Trends in neuromorphic technology
Open the PDF for Brains and bytes: Trends in neuromorphic technology in another window
Journal Articles

AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks

Vivswan Shah, Nathan Youngblood
Journal: APL Machine Learning
APL Mach. Learn. 1, 026116 (2023)
https://doi.org/10.1063/5.0134156
Published: June 2023
View article titled, AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks
Open the PDF for AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks in another window
Journal Articles

Pair distribution function analysis for oxide defect identification through feature extraction and supervised learning

Shuyan Zhang, Jie Gong, Sharon Chu, Daniel Z. Xiao, B. Reeja-Jayan, Alan J. H. McGaughey
Journal: APL Machine Learning
APL Mach. Learn. 1, 026115 (2023)
https://doi.org/10.1063/5.0130681
Published: June 2023
View article titled, Pair distribution function analysis for oxide defect identification through feature extraction and supervised learning
Open the PDF for Pair distribution function analysis for oxide defect identification through feature extraction and supervised learning in another window
Includes: Supplementary data
Journal Articles

Unsupervised machine learning discovery of structural units and transformation pathways from imaging data

Sergei V. Kalinin, Ondrej Dyck, Ayana Ghosh, Yongtao Liu, Bobby G. Sumpter, Maxim Ziatdinov
Journal: APL Machine Learning
APL Mach. Learn. 1, 026117 (2023)
https://doi.org/10.1063/5.0147316
Published: June 2023
View article titled, Unsupervised machine learning discovery of structural units and transformation pathways from imaging data
Open the PDF for Unsupervised machine learning discovery of structural units and transformation pathways from imaging data in another window
Journal Articles

Materials cartography: A forward-looking perspective on materials representation and devising better maps

Steven B. Torrisi, Martin Z. Bazant, Alexander E. Cohen, Min Gee Cho, Jens S. Hummelshøj, Linda Hung, Gaurav Kamat, Arash Khajeh, Adeesh Kolluru, Xiangyun Lei, Handong Ling, Joseph H. Montoya, Tim Mueller, Aini Palizhati, Benjamin A. Paren, Brandon Phan, Jacob Pietryga, Elodie Sandraz, Daniel Schweigert, Yang Shao-Horn, Amalie Trewartha, Ruijie Zhu, Debbie Zhuang, Shijing Sun
Journal: APL Machine Learning
APL Mach. Learn. 1, 020901 (2023)
https://doi.org/10.1063/5.0149804
Published: June 2023
View article titled, Materials cartography: A forward-looking perspective on materials representation and devising better maps
Open the PDF for Materials cartography: A forward-looking perspective on materials representation and devising better maps in another window
Journal Articles

Designing composition ratio of magnetic alloy multilayer for transverse thermoelectric conversion by Bayesian optimization

Naoki Chiba, Keisuke Masuda, Ken-ichi Uchida, Yoshio Miura
Journal: APL Machine Learning
APL Mach. Learn. 1, 026114 (2023)
https://doi.org/10.1063/5.0140332
Published: May 2023
View article titled, Designing composition ratio of magnetic alloy multilayer for transverse thermoelectric conversion by Bayesian optimization
Open the PDF for Designing composition ratio of magnetic alloy multilayer for transverse thermoelectric conversion by Bayesian optimization in another window
Includes: Supplementary data