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Schubert, T., & Schuh, W.-D. (2023). A Flexible Family of Compactly Supported Covariance Functions Based on Cutoff Polynomials. In J. T. Freymueller & L. Sánchez (Eds.), X Hotine-Marussi Symposium on Mathematical Geodesy (pp. 139–147). Springer International Publishing. https://doi.org/10.1007/1345_2023_200

Schuh, W.-D., Korte, J., Schubert, T., & Brockmann, J. M. (2023). Modeling of Inhomogeneous Spatio-Temporal Signals by Least Squares Collocation. In J. T. Freymueller & L. Sánchez (Eds.), X Hotine-Marussi Symposium on Mathematical Geodesy (pp. 149–158). Springer International Publishing. https://doi.org/10.1007/1345_2023_202

Brockmann, J. M., Schubert, T., & Schuh, W.-D. (2021). An Improved Model of the Earth’s Static Gravity Field Solely Derived from Reprocessed GOCE Data. Surveys in Geophysics, 42(2), 277–316. https://doi.org/10.1007/s10712-020-09626-0

Korte, J., Schubert, T., Brockmann, J. M., & Schuh, W.-D. (2021). A Mathematical Investigation of a Continuous Covariance Function Fitting with Discrete Covariances of an AR Process. Engineering Proceedings, 5(1), Article 1. https://doi.org/10.3390/engproc2021005018

Kvas, A., Brockmann, J. M., Krauss, S., Schubert, T., Gruber, T., Meyer, U., Mayer-Gürr, T., Schuh, W.-D., Jäggi, A., & Pail, R. (2021). GOCO06s – a satellite-only global gravity field model. Earth System Science Data, 13(1), 99–118. https://doi.org/https://doi.org/10.5194/essd-13-99-2021

Schubert, T., Brockmann, J. M., Korte, J., & Schuh, W.-D. (2021). On the Family of Covariance Functions Based on ARMA Models. Engineering Proceedings, 5(1), 37. https://doi.org/10.3390/engproc2021005037

Schubert, T., Brockmann, J. M., & Schuh, W.-D. (2021). Identification of Suspicious Data for Robust Estimation of Stochastic Processes. In P. Novák, M. Crespi, N. Sneeuw, & F. Sansò (Eds.), IX Hotine-Marussi Symposium on Mathematical Geodesy (pp. 199–207). Springer International Publishing. https://doi.org/10.1007/1345_2019_80

Schubert, T., Korte, J., Brockmann, J. M., & Schuh, W.-D. (2020). A Generic Approach to Covariance Function Estimation Using ARMA-Models. Mathematics, 8(4), 591. https://doi.org/10.3390/math8040591