Benedikt Soja
Orcid: 0000-0002-7010-2147
According to our database1,
Benedikt Soja
authored at least 18 papers
between 2021 and 2025.
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Collaborative distances:
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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
CoRR, 2024
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
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021