Yan Xu

Affiliations:
  • New Jersey Institute of Technology, Institute for Space Weather Sciences, Newark, NJ, USA


According to our database1, Yan Xu authored at least 31 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Deep Learning-Enabled Prediction of Geoeffective CMEs Using SOHO and SDO Observations.
CoRR, May, 2026

Daily Predictions of F10.7 and F30 Solar Indices with Deep Learning.
CoRR, April, 2026

Predicting Associations between Solar Flares and Coronal Mass Ejections Using SDO/HMI Magnetograms and a Hybrid Neural Network.
CoRR, April, 2026

2025
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model.
CoRR, March, 2025

Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model.
CoRR, March, 2025

Out-of-Sample Validation of MagNet.
Proceedings of the IEEE International Conference on Data Mining, 2025

2024
Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network.
CoRR, 2024

2023
Operational Prediction of Solar Flares Using a Transformer-Based Framework.
Dataset, November, 2023

Operational prediction of solar flares using a transformer-based framework.
Dataset, November, 2023

Operational prediction of solar flares using a transformer-based framework.
Dataset, November, 2023

Operational prediction of solar flares using a transformer-based framework.
Dataset, November, 2023

Operational prediction of solar flares using a transformer-based framework.
Dataset, November, 2023

Operational prediction of solar flares using a transformer-based framework.
Dataset, July, 2023

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, January, 2023

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, January, 2023

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, January, 2023

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, January, 2023

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, January, 2023

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, January, 2023

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, January, 2023

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, January, 2023

2022
Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, December, 2022

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks.
Dataset, December, 2022

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, December, 2022

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, December, 2022

Tracing Hα Fibrils through Bayesian Deep Learning.
Dataset, December, 2022

A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data.
CoRR, 2022

Inferring Line-of-Sight Velocities and Doppler Widths from Stokes Profiles of GST/NIRIS Using Stacked Deep Neural Networks.
CoRR, 2022

2021
Tracing Halpha Fibrils through Bayesian Deep Learning.
CoRR, 2021

2020
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations.
CoRR, 2020

Inferring Vector Magnetic Fields from Stokes Profiles of GST/NIRIS Using a Convolutional Neural Network.
CoRR, 2020


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