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Using Deep Learning to Create High-Fidelity Virtual Observations of the Solar Corona
2019
At NASA's Frontier Development Lab & the SETI Institute I've applied deep learning to solar data to create a high-fidelity virtual telescope that generates synthetic observations of the solar corona by image translation. Read moreWe achieved this via an encoder-decoder with skip connections (U-Net) that reconstructs the Sun's image of one instrument channel given temporally aligned images in three other channels. This work was accepted to the NeurIPS 2019 Machine Learning & the Physical Sciences Workshop. Learn More