Scholars@Duke
Ben Ren

Selected Publications

Heterogeneity and Memory Effect in the Sluggish Dynamics of Vacancy Defects in Colloidal Disordered Crystals and Their Implications to High-Entropy Alloys.

Journal Article Advanced science (Weinheim, Baden-Wurttemberg, Germany) · December 2022 Vacancy dynamics of high-density 2D colloidal crystals with a polydispersity in particle size are studied experimentally. Heterogeneity in vacancy dynamics is observed. Inert vacancies that hardly hop to other lattice sites and active vacancies that hop fr ... Full text Cite

Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications

Journal Article Remote Sensing · November 1, 2022 Transfer learning has been shown to be an effective method for achieving high-performance models when applying deep learning to remote sensing data. Recent research has demonstrated that representations learned through self-supervision transfer better than ... Full text Cite

Learning the Physics of All-Dielectric Metamaterials with Deep Lorentz Neural Networks

Journal Article Advanced Optical Materials · July 1, 2022 Deep neural networks (DNNs) have shown marked achievements across numerous research and commercial settings. Part of their success is due to their ability to “learn” internal representations of the input (x) that are ideal to attain an accurate approximati ... Full text Cite

Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning

Journal Article ISPRS International Journal of Geo-Information · April 1, 2022 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 power to a single household. A crucial resource for targeting further investm ... Full text Cite

Inverse deep learning methods and benchmarks for artificial electromagnetic material design

Journal Article · December 19, 2021 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 techniques have succeeded on a number of AEM design tasks, but to compare, con ... Link to item Cite

Benchmarking deep inverse models over time, and the neural-adjoint method

Conference Advances in Neural Information Processing Systems · January 1, 2020 Featured Publication We consider the task of solving generic inverse problems, where one wishes to determine the hidden parameters of a natural system that will give rise to a particular set of measurements. Recently many new approaches based upon deep learning have arisen, ge ... Cite