Beck, J., Liu, Y., von Schwerin, E., & Tempone, R. (2022). Goal-oriented adaptive finite element multilevel Monte Carlo with convergence rates. Computer Methods in Applied Mechanics and Engineering, 115582. https://doi.org/10.1016/j.cma.2022.115582

Beck, J., Liu, Y., von Schwerin, E., & Tempone, R. (2022). Goal-Oriented Adaptive Finite Element Multilevel Monte Carlo with Convergence Rates (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2206.10314

Beck, J., Mansour Dia, B., Espath, L., & Tempone, R. (2020). Multilevel double loop Monte Carlo and stochastic collocation methods with importance sampling for Bayesian optimal experimental design. International Journal for Numerical Methods in Engineering, 121(15), 3482–3503. Portico. https://doi.org/10.1002/nme.6367

Beck, J., Tamellini, L., & Tempone, R. (2019). IGA-based multi-index stochastic collocation for random PDEs on arbitrary domains. Computer Methods in Applied Mechanics and Engineering, 351, 330–350. https://doi.org/10.1016/j.cma.2019.03.042

Beck, J., Dia, B. M., Espath, L. F. R., Long, Q., & Tempone, R. (2018). Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain. Computer Methods in Applied Mechanics and Engineering, 334, 523–553. https://doi.org/10.1016/j.cma.2018.01.053

Beck, J., Tamellini, L., & Tempone, R. (2018). IGA-based Multi-Index Stochastic Collocation for random PDEs on arbitrary domains. ArXiv. https://doi.org/10.48550/ARXIV.1810.01661

Beck, J., Dia, B. M., Espath, L. F. R., & Tempone, R. (2018). Multilevel Double Loop Monte Carlo and Stochastic Collocation Methods with Importance Sampling for Bayesian Optimal Experimental Design. arXiv. https://doi.org/10.48550/ARXIV.1811.11469

Beck, J., Nobile, F., Tamellini, L., & Tempone, R. (2013). A Quasi-optimal Sparse Grids Procedure for Groundwater Flows. Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012, 1–16. https://doi.org/10.1007/978-3-319-01601-6_1

Beck, J., Nobile, F., Tamellini, L., & Tempone, R. (2014). Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients. Computers & Mathematics with Applications, 67(4), 732–751. https://doi.org/10.1016/j.camwa.2013.03.004

Beck, J., Tempone, R., Nobile, F., & Tamellini, L. (2012). On the optimal polynomial approximation of Stochastic PDEs by Galerkin and Collocation methods. Mathematical Models and Methods in Applied Sciences, 22(09), 1250023. https://doi.org/10.1142/s0218202512500236

Beck, J., Nobile, F., Tamellini, L., & Tempone, R. (2011). Implementation of optimal Galerkin and Collocation approximations of PDEs with Random Coefficients. ESAIM: Proceedings, 33, 10–21. https://doi.org/10.1051/proc/201133002

Bäck, J., Nobile, F., Tamellini, L., & Tempone, R. (2010). Stochastic Spectral Galerkin and Collocation Methods for PDEs with Random Coefficients: A Numerical Comparison. Spectral and High Order Methods for Partial Differential Equations, 43–62. https://doi.org/10.1007/978-3-642-15337-2_3