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Towards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparison

T. Xu, S. Xiao, S. Reuschen, N. Wildt, H. Franssen, and W. Nowak. Hydrology and Earth System Sciences, (2024 (submitted))

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Sebastian Brandhofer University of Stuttgart

Rigorous compilation for near-term quantum computersS. Brandhofer. Universität Stuttgart, Stuttgart, Dissertation, (2024)

Sebastian Friedl University of Stuttgart

Communication extension for cloud-based machine control of simulated robot processesF. Kretschmer, S. Friedl, A. Lechler, and A. Verl. 2016 IEEE International Conference on Industrial Technology (ICIT), page 54-58. (March 2016)

Sebastian Haunss

Dr. Sebastian Rojek University of Stuttgart

Sebastian Lippold University of Stuttgart

Other publications of authors with the same name

Towards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparisonT. Xu, S. Xiao, S. Reuschen, N. Wildt, H. Franssen, and W. Nowak. Hydrology and Earth System Sciences, (2024 (submitted))Search Space Representation and Reduction Methods to Enhance Multiobjective Water Supply Monitoring DesignF. Bode, P. Reed, S. Reuschen, and W. Nowak. Water Resources Research, 55 (3): 2257-2278 (2019)Hydraulically induced fracturing in heterogeneous porous media using a TPM-phase-ﬁeld model and geostatisticsA. Wagner, A. Sonntag, S. Reuschen, W. Nowak, and W. Ehlers. Proceedings in Applied Mathematics and Mechanics, (2023)Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMCS. Reuschen, T. Xu, and W. Nowak. Dataset, (2020)Related to: Reuschen, S., Xu, T., Nowak, W., 2020. Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC. Advances in Water Resources 141, 103614. doi: 10.1016/j.advwatres.2020.103614.Bayesian Inversion of Multi-Gaussian Log-Conductivity Fields With Uncertain Hyperparameters : An Extension of Preconditioned Crank-Nicolson Markov Chain Monte Carlo With Parallel TemperingS. Xiao, T. Xu, S. Reuschen, W. Nowak, and H. Hendricks-Franssen. Water resources research, 57 (9): e2021WR030313 (2021)Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMCS. Reuschen, T. Xu, and W. Nowak. Advances in water resources, 141 (July): 103614 (2020)Never Use the Complete Search Space: A Concept to Enhance the Optimization Procedure for Monitoring NetworksF. Bode, S. Reuschen, and W. Nowak. AGU fall meeting 2015, page IN11B-1774. Washington, DC, AGU, (2015)Hydraulically induced fracturing in heterogeneous porous media using a TPM-phase-field model and geostatisticsA. Wagner, A. Sonntag, S. Reuschen, W. Nowak, and W. Ehlers. 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), 23, 1, page e202200118. Wiley-VCH, (2023)Efficient Discretization-Independent Bayesian Inversion of High-Dimensional Multi-Gaussian Priors Using a Hybrid MCMCS. Reuschen, F. Jobst, and W. Nowak. Water resources research, 57 (8): e2021WR030051 (2021)Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC algorithmS. Reuschen, T. Xu, and W. Nowak. Advances in Water Resources, (2020)

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