10 citations as recorded by crossref.

1. Calibration of Dynamic Building Energy Models with Multiple Responses Using Bayesian Inference and Linear Regression Models Q. Li et al. https://doi.org/10.1016/j.egypro.2015.11.037
2. Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models K. Menberg et al. https://doi.org/10.1016/j.scitotenv.2020.140846
3. The influence and adjust method of hyperparameters’ prior distributions in Bayesian calibration for building stock energy prediction Y. Wang et al. https://doi.org/10.1016/j.enbuild.2022.112413
4. Bayesian calibration of building energy models with large datasets A. Chong et al. https://doi.org/10.1016/j.enbuild.2017.08.069
5. Guidelines for the Bayesian calibration of building energy models A. Chong & K. Menberg https://doi.org/10.1016/j.enbuild.2018.06.028
6. Continuous calibration of a digital twin: Comparison of particle filter and Bayesian calibration approaches R. Ward et al. https://doi.org/10.1017/dce.2021.12
7. Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods M. Girolami & B. Calderhead https://doi.org/10.1111/j.1467-9868.2010.00765.x
8. An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3 S. Phipps et al. https://doi.org/10.5194/gmd-14-5107-2021
9. Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning M. Kreitmair et al. https://doi.org/10.1017/dce.2022.32
10. Influence of error terms in Bayesian calibration of energy system models K. Menberg et al. https://doi.org/10.1080/19401493.2018.1475506