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Tomoko Matsuo
Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado BoulderMeeting roles in:
Machine Learning in Space Weather and Heliophysics I Oral
Machine Learning in Space Weather and Heliophysics II Poster
Equivalent Kernel Method for FUV Inversion Problems: Applications to NASA GOLD Disk Emission Data
Quantifying Storm-Time Neutral Density Uncertainties using a Physics-Based Particle Filter Framework
DYNAMIC - A Mission Concept to Advance Our Understanding of Orbital Space Weather
Why we need NASA’s DYNAMIC mission?: A Mission Crucial for Enabling the Prediction of Space Weather Impacts
Efforts Toward a Thermospheric Reanalysis during Storm-Time through Coupled Ionosphere-Thermosphere Data Assimilation
Hemispheric Asymmetries in Field-Aligned Currents: Principal Component and Assimilative Mapping Analysis of AMPERE, SuperMAG, and SuperDARN Data
Whole-Atmosphere Data Assimilation of GOLD FUV Observations
Estimation of auroral electron energy flux spectra from multispectral FUV satellite imagery
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