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

Remote sensing (Basel, Switzerland), 2022-08, Vol.14 (15), p.3547

2022

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Ultra-short-term prediction of LOD using LSTM neural networks

Journal of geodesy, 2023-05, Vol.97 (5), Article 52

2023

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Improvements and comparison of VLBI INT2 and INT3 session performance

Journal of geodesy, 2022-04, Vol.96 (4), Article 26

2022

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Discontinuity Detection in GNSS Station Coordinate Time Series Using Machine Learning

Remote sensing (Basel, Switzerland), 2021-10, Vol.13 (19), p.3906

2021

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Automated VLBI scheduling using AI-based parameter optimization

Journal of geodesy, 2021-05, Vol.95 (5), Article 58

2021

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Bridging astronomical, astrometric and geodetic scheduling for VGOS

Journal of geodesy, 2023-02, Vol.97 (2), Article 17

2023

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Short-term prediction of celestial pole offsets with interpretable machine learning

Earth, planets, and space, 2024-12, Vol.76 (1), p.18-15, Article 18

2024

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Optimal VLBI baseline geometry for UT1-UTC Intensive observations

Journal of geodesy, 2021, Vol.95 (7), p.75-75, Article 75

2021

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On the importance of accurate pole and station coordinates for VLBI Intensive baselines

Journal of geodesy, 2023-10, Vol.97 (10), Article 97

2023

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Global, spatially explicit modelling of zenith wet delay with XGBoost

Journal of geodesy, 2024, Vol.98 (4)

2024

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Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach

Remote sensing (Basel, Switzerland), 2022-01, Vol.14 (1), p.17

2022

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Modeling the Differences between Ultra-Rapid and Final Orbit Products of GPS Satellites Using Machine-Learning Approaches

Remote sensing (Basel, Switzerland), 2023-12, Vol.15 (23), p.5585

2023

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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 sensing (Basel, Switzerland), 2023-12, Vol.15 (24), p.5762

2023

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Assessment of length-of-day and universal time predictions based on the results of the Second Earth Orientation Parameters Prediction Comparison Campaign

Journal of geodesy, 2024-03, Vol.98 (3)

2024

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Collecting volunteered geographic information from the Global Navigation Satellite System (GNSS): experiences from the CAMALIOT project

International journal of digital earth, 2023-12, Vol.16 (1), p.2818-2841

2023

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JTRF2014, the JPL Kalman filter and smoother realization of the International Terrestrial Reference System

Journal of geophysical research. Solid earth, 2017-10, Vol.122 (10), p.8474-8510

2017

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Machine learning-based multipath modeling in spatial domain applied to GNSS short baseline processing

GPS solutions, 2024, Vol.28 (1), p.9, Article 9

2024

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Inclusion of data uncertainty in machine learning and its application in geodetic data science, with case studies for the prediction of Earth orientation parameters and GNSS station coordinate time series

Advances in space research, 2022-08, Vol.70 (3), p.563-575

2022

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Uncertainty Quantification for Machine Learning‐Based Ionosphere and Space Weather Forecasting: Ensemble, Bayesian Neural Network, and Quantile Gradient Boosting

Space weather, 2023-10, Vol.21 (10)

2023

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Smartphone-based Vision/MEMS-IMU/GNSS tightly coupled seamless positioning using factor graph optimization

Measurement : journal of the International Measurement Confederation, 2024-04, Vol.229, Article 114420

2024

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Detecting Signatures of Convective Storm Events in GNSS‐SNR: Two Case Studies From Summer 2021 in Switzerland

Geophysical research letters, 2023-11, Vol.50 (21), p.n/a

2023

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Deep ensemble geophysics-informed neural networks for the prediction of celestial pole offsets

Geophysical journal international, 2023-11, Vol.236 (1), p.480-493

2023

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Uncertainties of Interpolating Satellite-Specific Slant Ionospheric Delays and Impacts on PPP-RTK

IEEE transactions on aerospace and electronic systems, 2024-02, p.1-16

2024

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Tightly coupled integration of monocular visual-inertial odometry and UC-PPP based on factor graph optimization in difficult urban environments

GPS solutions, 2024, Vol.28 (1), p.45, Article 45

2024

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Application of Kalman filtering in VLBI data analysis

Earth, planets, and space, 2015-08, Vol.67 (1), p.1-9, Article 136

2015

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

Ultra-short-term prediction of LOD using LSTM neural networks

Improvements and comparison of VLBI INT2 and INT3 session performance

Discontinuity Detection in GNSS Station Coordinate Time Series Using Machine Learning

Automated VLBI scheduling using AI-based parameter optimization

Bridging astronomical, astrometric and geodetic scheduling for VGOS

Short-term prediction of celestial pole offsets with interpretable machine learning

Optimal VLBI baseline geometry for UT1-UTC Intensive observations

On the importance of accurate pole and station coordinates for VLBI Intensive baselines

Global, spatially explicit modelling of zenith wet delay with XGBoost

Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach

Modeling the Differences between Ultra-Rapid and Final Orbit Products of GPS Satellites Using Machine-Learning Approaches

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

Assessment of length-of-day and universal time predictions based on the results of the Second Earth Orientation Parameters Prediction Comparison Campaign

Collecting volunteered geographic information from the Global Navigation Satellite System (GNSS): experiences from the CAMALIOT project

JTRF2014, the JPL Kalman filter and smoother realization of the International Terrestrial Reference System

Machine learning-based multipath modeling in spatial domain applied to GNSS short baseline processing

Inclusion of data uncertainty in machine learning and its application in geodetic data science, with case studies for the prediction of Earth orientation parameters and GNSS station coordinate time series

Uncertainty Quantification for Machine Learning‐Based Ionosphere and Space Weather Forecasting: Ensemble, Bayesian Neural Network, and Quantile Gradient Boosting

Smartphone-based Vision/MEMS-IMU/GNSS tightly coupled seamless positioning using factor graph optimization

Detecting Signatures of Convective Storm Events in GNSS‐SNR: Two Case Studies From Summer 2021 in Switzerland

Deep ensemble geophysics-informed neural networks for the prediction of celestial pole offsets

Uncertainties of Interpolating Satellite-Specific Slant Ionospheric Delays and Impacts on PPP-RTK

Tightly coupled integration of monocular visual-inertial odometry and UC-PPP based on factor graph optimization in difficult urban environments

Application of Kalman filtering in VLBI data analysis

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