Speaker: Eve Armstrong Institution: New York Institute of Technology, Manhattan Campus Title: "Predicting the Behavior of Sparsely-Sampled Systems Across Astrophysics, Neurobiology, and Epidemiology” Abstract: Inference is a term that encompasses many techniques including machine learning and statistical data assimilation (SDA). Unlike machine learning, which harnesses predictive power from extremely large data sets, SDA is designed for…
Measurement and quasi-classical modeling of spin density evolution and spin correlation in a Fermi gas
Development of Electronics and Simulations for the nEDM@SNS Experiment
Measuring the Coherent Elastic Neutrino-Neutron Scattering Cross Section in Germanium
Measurement of Coherent Elastic Neutrino Nucleus Scattering on Germanium at the SNS
Identifying precursors of creeping landslides through remote sensing and network science
Techniques for the quantum few-body problem in nuclear structure calculations
Searching for breakdown of classical spin wave models in a weakly-interacting Fermi gas