Analytical electron microscopy and spectroscopy of biological specimens, polymers, and
other beam sensitive materials has been a challenging area due to irradiation damage.
There is a pressing need to develop novel imaging and spectroscopic imaging methods that
will minimize such sample damage as well as reduce the data acquisition time. The latter is
useful for high-throughput analysis of materials structure and chemistry. In this work, we
present a novel machine learning based method for dynamic sparse sampling of EDS data …