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Copy file name to clipboardExpand all lines: README.md
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@@ -11,29 +11,25 @@ The available models cover two main use-cases:
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The above use cases have been explored in the following publications:
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* "Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translation"
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Accepted for publication on ApJ (2022)
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*["Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translation"](https://iopscience.iop.org/article/10.3847/1538-4357/ac867b/meta)
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ApJ 937 100 (2022)
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*["Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning"](https://www.aanda.org/articles/aa/abs/2021/04/aa40051-20/aa40051-20.html)
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A&A 648, A53 (2021)
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* "Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning"
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A&A 648, A53 (2021)
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https://arxiv.org/abs/2012.14023.
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* "Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning"
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NeurIPS 2019 - ML4PS Workshop
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https://arxiv.org/abs/1911.04008
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* "Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona"
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ML4PS NeurIPS 2019 - ML4PS Workshop
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https://arxiv.org/abs/1911.04006
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All the results can be reproduced with the code in this repo.
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*["Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning"](https://arxiv.org/abs/1911.04008)
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NeurIPS 2019 - ML4PS Workshop
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*["Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona"](https://arxiv.org/abs/1911.04006)
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NeurIPS 2019 - ML4PS Workshop
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All the results can be reproduced with the code contained in this repo.
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The data uncorrected for degradation used in the [autocalibration paper](https://arxiv.org/abs/1911.04008) is
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available [here](https://zenodo.org/record/4430801#.X_xiP-lKhmE).
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# How to use the repo
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1# How to use the repo
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1) Reusable code lives inside src in the form of a package called sdo that can be installed.
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In order to install the package:
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This project started as part of the [2019 Frontier Development Lab (FDL) SDO team](https://frontierdevelopmentlab.org/2019-sdo).
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A description of this program is available [here](https://frontierdevelopmentlab.org/about-1).
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# Citations
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If you decide to reuse this code, please cite [](https://doi.org/10.5281/zenodo.6954828)
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