SEMNet: A deep learning tool for reconstructing long-term solar EUV irradiance with uncertainty quantification.
References: Reconstruction of Solar Extreme-ultraviolet Irradiance Using Ca II K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification. Haodi Jiang et al 2025 ApJS 280 50. https://iopscience.iop.org/article/10.3847/1538-4357/ac927e
MagNet: A deep learning tool for generating vector megnetorgrams for SOHO/MDI
References: Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data with Deep Learning. Sol Phys 298, 87 (2023). https://doi.org/10.1007/s11207-023-02180-z. https://link.springer.com/article/10.1007/s11207-023-02180-z#citeas
SDNN: A tool is designed to perform Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
References: Inferring Line-of-sight Velocities and Doppler Widths from Stokes Profiles of GST/ NIRIS Using Stacked Deep Neural Networks. Haodi Jiang et al 2022 ApJ 939 66. https://iopscience.iop.org/article/10.3847/1538-4357/ac927e
FibrilNet: A deep learning tool for tracing H-alpha fibril of solar observations.
References: Tracing Hα Fibrils through Bayesian Deep Learning. Haodi Jiang et al 2021 ApJS 256 20. https://iopscience.iop.org/article/10.3847/1538-4365/ac14b7
SolarUnet: A deep learning tool for identifying and tracking solar magnetic flux elements.
References: Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. Jiang, H., Wang, J., Liu, C., et al. 2020, ApJS, 250. https://iopscience.iop.org/article/10.3847/1538-4365/aba4aa