Leader of the group Scientific Computing: Benjamin Sanderse.
Vacancies
No vacancies currently.
News
Members
Associated Members
Publications
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Jansson, F.R, van den Oord, G, Pelupessy, F.I, Chertova, M, Grönqvist, J.H, Siebesma, A.P, & Crommelin, D.T. (2022). Representing cloud mesoscale variability in superparameterized climate models. Journal of Advances in Modeling Earth Systems, 14(8), e2021MS002892.1–e2021MS002892.16. doi:10.1029/2021MS002892
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Bronik, K, Roa, W.M, Vassaux, M, Edeling, W.N, & Coveney, P.V. (2022). Automated variance-based sensitivity analysis of a heterogeneous atomistic-continuum system. In Proceedings of ICCS 2022 (pp. 762–766). doi:10.1007/978-3-031-08760-8_62
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van der Meer, R, Oosterlee, C.W, & Borovykh, A.I. (2022). Optimally weighted loss functions for solving PDEs with Neural Networks. Journal of Computational and Applied Mathematics, 405. doi:10.1016/j.cam.2021.113887
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Sanderse, B, Dighe, V.V, Boorsma, K, & Schepers, J.G. (2022). Efficient Bayesian calibration of aerodynamic wind turbine models using surrogate modeling. Wind Energy Science, 7(2), 759–781. doi:10.5194/wes-7-759-2022
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Andersson, K.H, & Oosterlee, C.W. (2021). Deep learning for CVA computations of large portfolios of financial derivatives. Applied Mathematics and Computation, 409. doi:10.1016/j.amc.2021.126399
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Salvador Mancho, B, & Oosterlee, C.W. (2021). Corrigendum to “Total value adjustment for a stochastic volatility model. A comparison with the Black–Scholes model”. Applied Mathematics and Computation, 406. doi:10.1016/j.amc.2021.125999
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van den Bos, L.M.M, & Sanderse, B. (2021). A geometrical interpretation of the addition of nodes to an interpolatory quadrature rule while preserving positive weights. Journal of Computational and Applied Mathematics, 391. doi:10.1016/j.cam.2021.113430
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Souto Arias, L.A, & Cirillo, P. (2021). Joint and survivor annuity valuation with a bivariate reinforced urn process. Insurance: Mathematics and Economics, 99, 174–189. doi:10.1016/j.insmatheco.2021.04.004
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Suleimenova, D, Arabnejad, H, Edeling, W.N, & Groen, D. (2021). Sensitivity-driven simulation development: A case study in forced migration. Philosophical Transactions of the Royal Society A , 379(2197). doi:10.1098/rsta.2020.0077
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Kelbij Star, S.K, Sanderse, B, Stabile, G, Rozza, G, & Degroote, J. (2021). Reduced order models for the incompressible Navier-Stokes equations on collocated grids using a ‘discretize-then-project’ approach. International Journal for Numerical Methods in Fluids, 93(8), 2694–2722. doi:10.1002/fld.4994
Current projects with external funding
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Valuation Adjustments for Improved Risk Management (ABC-EU-XVA)
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Physics based ICT: The digital twin in pipelines (DP-Trans)
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Learning small closure models for large multiscale problems. (None)
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Robust numerical modelling for transient multiphase CO2 transport (SHELL)
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Unravelling Neural Networks with Structure-Preserving Computing (Unravelling Neural Networks)
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Discretize first, reduce next: a new paradigm to closure for fluid flow simulation (Vidi Sanderse)
Related partners
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Shell, Amsterdam
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MeitY
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Technische Universiteit Eindhoven
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Universiteit Leiden