198 citations · 232 across the 7 of their papers we have counts for
7 papers
Deep Generalized Green's Functions
Rixi Peng, Juncheng Dong, Jordan Malof +2
In this study, we address the challenge of obtaining a Green's function operator for linear partial differential equations (PDEs). The Green's function is well-sought after due to…
Machine Learning for Mie-Tronics
Wenhao Li, Hooman Barati Sedeh, Willie J. Padilla +3
Electromagnetic multipole expansion theory underpins nanoscale light-matter interactions, particularly within subwavelength meta-atoms, paving the way for diverse and captivating o…
Meta-simulation for the Automated Design of Synthetic Overhead Imagery
Handi Yu, Simiao Ren, Leslie M. Collins +1
The use of synthetic (or simulated) data for training machine learning models has grown rapidly in recent years. Synthetic data can often be generated much faster and more cheaply…
Utilizing geospatial data for assessing energy security: Mapping small solar home systems using unmanned aerial vehicles and deep learning
Simiao Ren, Jordan Malof, T. Robert Fetter +3
Solar home systems (SHS), a cost-effective solution for rural communities far from the grid in developing countries, are small solar panels and associated equipment that provides p…
Inverse deep learning methods and benchmarks for artificial electromagnetic material design
Simiao Ren, Ashwin Mahendra, Omar Khatib +3
Deep learning (DL) inverse techniques have increased the speed of artificial electromagnetic material (AEM) design and improved the quality of resulting devices. Many DL inverse te…
On Choosing Training and Testing Data for Supervised Algorithms in Ground Penetrating Radar Data for Buried Threat Detection
Daniël Reichman, Leslie M. Collins, Jordan M. Malof
Ground penetrating radar (GPR) is one of the most popular and successful sensing modalities that has been investigated for landmine and subsurface threat detection. Many of the det…