Kees Oosterlee

Kumar, P, Rodrigo, C, Gaspar, F.J, & Oosterlee, C.W. (2019). On local Fourier analysis of multigrid methods for PDEs with jumping and random coefficients. SIAM Journal on Scientific Computing, 41(3), A1385–A1413. doi:10.1137/18M1173769

Jain, S, Leitao Rodriguez, Á, & Oosterlee, C.W. (2019). Rolling Adjoints: Fast Greeks along Monte Carlo scenarios for early-exercise options. Journal of Computational Science, 33, 95–112. doi:10.1016/j.jocs.2019.03.001

Le Floc’h, F.L, & Oosterlee, C.W. (2019). Model-free stochastic collocation for an arbitrage-free implied volatility, part II. Risks, 7(1). doi:10.3390/risks7010030

Liu, S, Oosterlee, C.W, & Bohte, S.M. (2019). Pricing options and computing implied volatilities using neural networks. Risks, 7(1). doi:10.3390/risks7010016

Suárez-Taboada, M, Witteveen, J.A.S, Grzelak, L.A, & Oosterlee, C.W. (2018). Uncertainty quantification and Heston model. Journal of Mathematics in Industry, 8(1). doi:10.1186/s13362-018-0047-2

von Sydow, L, Milovanović, S, Larsson, E, In't Hout, K, Wiktorsson, M, Oosterlee, C.W, … Waldén, J. (2018). BENCHOP–SLV: the BENCHmarking project in Option Pricing–Stochastic and Local Volatility problems. International Journal of Computer Mathematics. doi:10.1080/00207160.2018.1544368

Borovykh, A.I, Bohte, S.M, & Oosterlee, C.W. (2018). Dilated convolutional neural networks for time series forecasting. Journal of Computational Finance. doi:10.21314/JCF.2019.358

Kumar, P, Luo, P, Gaspar, F.J, & Oosterlee, C.W. (2018). A multigrid multilevel Monte Carlo method for transport in the Darcy–Stokes system. Journal of Computational Physics, 371, 382–408. doi:10.1016/j.jcp.2018.05.046

Grzelak, L.A, Witteveen, J.A.S, Suárez-Taboada, M, & Oosterlee, C.W. (2018). The stochastic collocation Monte Carlo sampler: highly efficient sampling from ‘expensive’ distributions. Quantitative Finance. doi:10.1080/14697688.2018.1459807

Sanderse, B, Misra, S, Dubinkina, S, Henkes, R.A.W.M, & Oosterlee, C.W. (2018). Numerical simulation of roll waves in pipelines using the two-fluid model. In 11th North American Conference on Multiphase Technology (pp. 373–386).