3 papers
cs.LG2025
Contrast transfer functions help quantify neural network out-of-distribution generalization in HRTEM
Luis Rangel DaCosta, Mary C. Scott
Neural networks, while effective for tackling many challenging scientific tasks, are not known to perform well out-of-distribution (OOD), i.e., within domains which differ from the…
nucl-th2023
pynucastro 2.1: an update on the development of a python library for nuclear astrophysics
Alexander Smith Clark, Eric T. Johnson, Zhi Chen +5
pynucastro is a python library that provides visualization and analyze techniques to classify, construct, and evaluate nuclear reaction rates and networks. It provides tools that a…
cond-mat.mtrl-sci2023
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…