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Kristoffer G. van der Zee
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2020 – today
- 2024
- [j20]Ignacio Brevis
, Ignacio Muga
Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. Comput. Math. Appl. 164: 139-149 (2024) - [j19]Yiyun Fan, John Billingham
A Shape-Newton Method for Free-Boundary Problems Subject to the Bernoulli Boundary Condition. SIAM J. Sci. Comput. 46(6): 3599- (2024) - 2023
- [j18]Jessica Zhang, John A. Evans, Héctor Gómez
An editorial perspective: recent updates of EWCO and submission guidelines. Eng. Comput. 39(1): 1-2 (2023) - [j17]Jelena Ninic
Editorial UKACM 2022: advances in computational mechanics. Eng. Comput. 39(6): 3739-3741 (2023) - [j16]Massimo Sferza
Global-local multidisciplinary optimisation for the evaluation of local constraints on finer meshes in preliminary aircraft design. Eng. Comput. 39(6): 4167-4184 (2023) - [i8]Ignacio Brevis, Ignacio Muga, David Pardo, Oscar A. Rodríguez, Kristoffer G. van der Zee:
Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. CoRR abs/2304.01722 (2023) - [i7]Yiyun Fan, John Billingham, Kristoffer G. van der Zee:
A Shape-Newton Method for Free-boundary Problems Subject to The Bernoulli Boundary Condition. CoRR abs/2305.14254 (2023) - 2022
- [j15]Jessica Zhang, John A. Evans, Héctor Gómez
An editorial perspective: new team, aims and scope and advances of EWCO. Eng. Comput. 38(1): 1 (2022) - [j14]Felipe Millar, Ignacio Muga, Sergio Rojas
Projection in negative norms and the regularization of rough linear functionals. Numerische Mathematik 150(4): 1087-1121 (2022) - [j13]Paul Houston, Connor J. Rourke, Kristoffer G. van der Zee
Linearization of the Travel Time Functional in Porous Media Flows. SIAM J. Sci. Comput. 44(3): 531- (2022) - [i6]Ignacio Brevis, Ignacio Muga, Kristoffer G. van der Zee:
Neural Control of Discrete Weak Formulations: Galerkin, Least-Squares and Minimal-Residual Methods with Quasi-Optimal Weights. CoRR abs/2206.07475 (2022) - 2021
- [j12]Ignacio Brevis
A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations. Comput. Math. Appl. 95: 186-199 (2021) - [i5]Felipe Millar, Ignacio Muga, Sergio Rojas, Kristoffer G. van der Zee:
Projection in negative norms and the regularization of rough linear functionals. CoRR abs/2101.03044 (2021) - [i4]Paul Houston, Connor J. Rourke, Kristoffer G. van der Zee:
Linearisation of the Travel Time Functional in Porous Media Flows. CoRR abs/2111.15504 (2021) - 2020
- [j11]Paul Houston, Sarah Roggendorf
Eliminating Gibbs phenomena: A non-linear Petrov-Galerkin method for the convection-diffusion-reaction equation. Comput. Math. Appl. 80(5): 851-873 (2020) - [j10]Ignacio Muga, Kristoffer G. van der Zee
Discretization of Linear Problems in Banach Spaces: Residual Minimization, Nonlinear Petrov-Galerkin, and Monotone Mixed Methods. SIAM J. Numer. Anal. 58(6): 3406-3426 (2020) - [i3]Ignacio Brevis, Ignacio Muga, Kristoffer G. van der Zee:
Data-Driven Finite Elements Methods: Machine Learning Acceleration of Goal-Oriented Computations. CoRR abs/2003.04485 (2020)
2010 – 2019
- 2019
- [j9]Paul Houston, Ignacio Muga
The Convection-Diffusion-Reaction Equation in Non-Hilbert Sobolev Spaces: A Direct Proof of the Inf-Sup Condition and Stability of Galerkin's Method. Comput. Methods Appl. Math. 19(3): 503-522 (2019) - [j8]Ignacio Muga
The Discrete-Dual Minimal-Residual Method (DDMRes) for Weak Advection-Reaction Problems in Banach Spaces. Comput. Methods Appl. Math. 19(3): 557-579 (2019) - [i2]Paul Houston, Sarah Roggendorf, Kristoffer G. van der Zee:
Eliminating Gibbs Phenomena: A Non-linear Petrov-Galerkin Method for the Convection-Diffusion-Reaction Equation. CoRR abs/1908.00996 (2019) - [i1]Paul Houston, Sarah Roggendorf, Kristoffer G. van der Zee:
Gibbs Phenomena for Lq-Best Approximation in Finite Element Spaces - Some Examples. CoRR abs/1909.00658 (2019) - 2018
- [j7]Robert Dyja
Parallel-In-Space-Time, Adaptive Finite Element Framework for Nonlinear Parabolic Equations. SIAM J. Sci. Comput. 40(3) (2018) - [j6]X. Wu, Kris G. van der Zee
A Posteriori Error Estimation and Adaptivity for Nonlinear Parabolic Equations using IMEX-Galerkin Discretization of Primal and Dual Equations. SIAM J. Sci. Comput. 40(5): A3371-A3399 (2018) - 2016
- [j5]Michael Feischl
An Abstract Analysis of Optimal Goal-Oriented Adaptivity. SIAM J. Numer. Anal. 54(3): 1423-1448 (2016) - 2014
- [j4]Vikram V. Garg, Serge Prudhomme, Kris G. van der Zee, Graham F. Carey:
Adjoint-consistent formulations of slip models for coupled electroosmotic flow systems. Adv. Model. Simul. Eng. Sci. 1(1): 15:1-15:29 (2014) - 2010
- [j3]Kris G. van der Zee, E. H. van Brummelen
Goal-Oriented Error Estimation and Adaptivity for Free-Boundary Problems: The Domain-Map Linearization Approach. SIAM J. Sci. Comput. 32(2): 1064-1092 (2010) - [j2]Kris G. van der Zee, E. H. van Brummelen
Goal-Oriented Error Estimation and Adaptivity for Free-Boundary Problems: The Shape-Linearization Approach. SIAM J. Sci. Comput. 32(2): 1093-1118 (2010)
2000 – 2009
- 2006
- [j1]Kris G. van der Zee, E. H. van Brummelen
An H1(Ph)-Coercive Discontinuous Galerkin Formulation for the Poisson Problem: 1D Analysis. SIAM J. Numer. Anal. 44(6): 2671-2698 (2006)
Coauthor Index
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