Hammouda, C. B., Rezvanova, E., von Schwerin, E., & Tempone, R. (2023). Lagrangian Relaxation for Continuous-Time Optimal Control of Coupled Hydrothermal Power Systems Including Storage Capacity and a Cascade of Hydropower Systems with Time Delays (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2311.00794

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

Ballesio, M., Jasra, A., von Schwerin, E., & Tempone, R. (2022). A Wasserstein coupled particle filter for multilevel estimation. Stochastic Analysis and Applications, 1–40. https://doi.org/10.1080/07362994.2022.2081181

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

Ballesio, M., Beck, J., Pandey, A., Parisi, L., von Schwerin, E., & Tempone, R. (2019). Multilevel Monte Carlo acceleration of seismic wave propagation under uncertainty. GEM - International Journal on Geomathematics, 10(1). https://doi.org/10.1007/s13137-019-0135-5

Haji-Ali, A.-L., Nobile, F., von Schwerin, E., & Tempone, R. (2015). Optimization of mesh hierarchies in multilevel Monte Carlo samplers. Stochastics and Partial Differential Equations Analysis and Computations, 4(1), 76–112. https://doi.org/10.1007/s40072-015-0049-7

Collier, N., Haji-Ali, A.-L., Nobile, F., von Schwerin, E., & Tempone, R. (2014). A continuation multilevel Monte Carlo algorithm. BIT Numerical Mathematics, 55(2), 399–432. https://doi.org/10.1007/s10543-014-0511-3

Bayer, C., Hoel, H., von Schwerin, E., & Tempone, R. (2014). On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations. SIAM Journal on Scientific Computing, 36(2), A869–A885. https://doi.org/10.1137/130911433

Migliorati, G., Nobile, F., von Schwerin, E., & Tempone, R. (2014). Analysis of Discrete $$L^2$$ L 2 Projection on Polynomial Spaces with Random Evaluations. Foundations of Computational Mathematics. https://doi.org/10.1007/s10208-013-9186-4

Hoel, H., von Schwerin, E., Szepessy, A., & Tempone, R. (2014). Implementation and analysis of an adaptive multilevel Monte Carlo algorithm. Monte Carlo Methods and Applications, 20(1), 1–41. https://doi.org/10.1515/mcma-2013-0014

Migliorati, G., Nobile, F., von Schwerin, E., & Tempone, R. (2013). Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces. SIAM Journal on Scientific Computing, 35(3), A1440–A1460. https://doi.org/10.1137/120897109

Moon, K.-S., von Schwerin, E., Szepessy, A., & Tempone, R. (2005). An adaptive algorithm for ordinary, stochastic and partial differential equations. Contemporary Mathematics, 325–343. https://doi.org/10.1090/conm/383/07176

Hoel, H., von Schwerin, E., Szepessy, A., & Tempone, R. (2011). Adaptive Multilevel Monte Carlo Simulation. Lecture Notes in Computational Science and Engineering, 217–234. https://doi.org/10.1007/978-3-642-21943-6_10

von Schwerin, E., & Szepessy, A. (2010). A stochastic phase-field model determined from molecular dynamics. ESAIM: Mathematical Modelling and Numerical Analysis, 44(4), 627–646. https://doi.org/10.1051/m2an/2010022

Moon, K.-S., von Schwerin, E., Szepessy, A., & Tempone, R. (2006). Convergence Rates for an Adaptive Dual Weighted Residual Finite Element Algorithm. BIT Numerical Mathematics, 46(2), 367–407. https://doi.org/10.1007/s10543-006-0058-z

Dzougoutov, A., Moon, K.-S., von Schwerin, E., Szepessy, A., & Tempone, R. (2005). Adaptive Monte Carlo Algorithms for Stopped Diffusion. Multiscale Methods in Science and Engineering, 59–88. https://doi.org/10.1007/3-540-26444-2_3