Benedikt Soja

Orcid: 0000-0002-7010-2147

According to our database1, Benedikt Soja authored at least 18 papers between 2021 and 2025.

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

Timeline

2021
2022
2023
2024
2025
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7
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
HDTM: A Novel Model Providing Hydrostatic Delay and Weighted Mean Temperature for Real-Time GNSS Precipitable Water Vapor Retrieval.
IEEE Trans. Geosci. Remote. Sens., 2025

Laplacian deep ensembles: Methodology and application in predicting dUT1 considering geophysical fluids.
Comput. Geosci., 2025

2024
Uncertainties of Interpolating Satellite-Specific Slant Ionospheric Delays and Impacts on PPP-RTK.
IEEE Trans. Aerosp. Electron. Syst., February, 2024

A New Deep-Learning-Assisted Global Water Vapor Stratification Model for GNSS Meteorology: Validations and Applications.
IEEE Trans. Geosci. Remote. Sens., 2024

Forecasting of Tropospheric Delay Using AI Foundation Models in Support of Microwave Remote Sensing.
IEEE Trans. Geosci. Remote. Sens., 2024

Uncertainties of Satellite-based Essential Climate Variables from Deep Learning.
CoRR, 2024

Global Ionospheric Modeling Using Multi-GNSS: A Machine Learning Approach.
Proceedings of the IGARSS 2024, 2024

Modelling the Troposphere with Global Navigation Satellite Systems, Meteorological Data and Machine Learning.
Proceedings of the IGARSS 2024, 2024

2023
Modeling the Differences between Ultra-Rapid and Final Orbit Products of GPS Satellites Using Machine-Learning Approaches.
Remote. Sens., December, 2023

Analyzing the Ionospheric Irregularities Caused by the September 2017 Geomagnetic Storm Using Ground-Based GNSS, Swarm, and FORMOSAT-3/COSMIC Data near the Equatorial Ionization Anomaly in East Africa.
Remote. Sens., December, 2023

Collecting volunteered geographic information from the Global Navigation Satellite System (GNSS): experiences from the CAMALIOT project.
Int. J. Digit. Earth, December, 2023

Machine Learning-Based Exploitation of Crowdsourced GNSS Data for Atmospheric Studies.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach.
Remote. Sens., 2022

Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting.
Remote. Sens., 2022

Data Driven Approaches for the Prediction of Earth's Effective Angular Momentum Functions.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021
Discontinuity Detection in GNSS Station Coordinate Time Series Using Machine Learning.
Remote. Sens., 2021

Small Geodetic Datasets and Deep Networks: Attention-Based Residual LSTM Autoencoder Stacking for Geodetic Time Series.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Modified Deep Transformers for GNSS Time Series Prediction.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021


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