87 citations · 131 across the 5 of their papers we have counts for
5 papers
A robust synthetic data generation framework for machine learning in High-Resolution Transmission Electron Microscopy (HRTEM)
Luis Rangel DaCosta, Katherine Sytwu, Catherine Groschner +1
Machine learning techniques are attractive options for developing highly-accurate automated analysis tools for nanomaterials characterization, including high-resolution transmissio…
Generalization Across Experimental Parameters in Machine Learning Analysis of High Resolution Transmission Electron Microscopy Datasets
Katherine Sytwu, Luis Rangel DaCosta, Mary C. Scott
Neural networks are promising tools for high-throughput and accurate transmission electron microscopy (TEM) analysis of nanomaterials, but are known to generalize poorly on data th…
Understanding the Influence of Receptive Field and Network Complexity in Neural-Network-Guided TEM Image Analysis
Katherine Sytwu, Catherine Groschner, Mary C. Scott
Trained neural networks are promising tools to analyze the ever-increasing amount of scientific image data, but it is unclear how to best customize these networks for the unique fe…
Driving energetically-unfavorable dehydrogenation dynamics with plasmonics
Katherine Sytwu, Michal Vadai, Fariah Hayee +4
Nanoparticle surface structure and geometry generally dictate where chemical transformations occur, with the low-coordination-number, high-radius-of-curvature sites being energetic…
Weakly Explosive Percolation in Directed Networks
Shane Squires, Katherine Sytwu, Diego Alcala +3
Percolation, the formation of a macroscopic connected component, is a key feature in the description of complex networks. The dynamical properties of a variety of systems can be un…