An H1(Ph)-Coercive Discontinuous Galerkin Formulation for the Poisson Problem: 1D Analysis. - Kris G. van der Zee; E. H. van Brummelen; René de Borst (SIAM J. Numer. Anal., 2006)

Goal-Oriented Error Estimation and Adaptivity for Free-Boundary Problems: The Domain-Map Linearization Approach. - Kris G. van der Zee; E. H. van Brummelen; René de Borst (SIAM J. Sci. Comput., 2010)

Goal-Oriented Error Estimation and Adaptivity for Free-Boundary Problems: The Shape-Linearization Approach. - Kris G. van der Zee; E. H. van Brummelen; René de Borst (SIAM J. Sci. Comput., 2010)

Adjoint-consistent formulations of slip models for coupled electroosmotic flow systems. - Vikram V. Garg; Serge Prudhomme; Kris G. van der Zee; Graham F. Carey (Adv. Model. Simul. Eng. Sci., 2014)

An Abstract Analysis of Optimal Goal-Oriented Adaptivity. - Michael Feischl; Dirk Praetorius; Kristoffer G. van der Zee (SIAM J. Numer. Anal., 2016)

Parallel-In-Space-Time, Adaptive Finite Element Framework for Nonlinear Parabolic Equations. - Robert Dyja; Baskar Ganapathysubramanian; Kristoffer G. van der Zee (SIAM J. Sci. Comput., 2018)

A Posteriori Error Estimation and Adaptivity for Nonlinear Parabolic Equations using IMEX-Galerkin Discretization of Primal and Dual Equations. - X. Wu; Kris G. van der Zee; Görkem Simsek-Senel; E. H. van Brummelen (SIAM J. Sci. Comput., 2018)

The Convection-Diffusion-Reaction Equation in Non-Hilbert Sobolev Spaces: A Direct Proof of the Inf-Sup Condition and Stability of Galerkin's Method. - Paul Houston; Ignacio Muga; Sarah Roggendorf; Kristoffer G. van der Zee (Comput. Methods Appl. Math., 2019)

The Discrete-Dual Minimal-Residual Method (DDMRes) for Weak Advection-Reaction Problems in Banach Spaces. - Ignacio Muga; Matthew J. W. Tyler; Kristoffer G. van der Zee (Comput. Methods Appl. Math., 2019)

Gibbs Phenomena for Lq-Best Approximation in Finite Element Spaces - Some Examples. - Paul Houston; Sarah Roggendorf; Kristoffer G. van der Zee (CoRR, 2019)

Eliminating Gibbs phenomena: A non-linear Petrov-Galerkin method for the convection-diffusion-reaction equation. - Paul Houston; Sarah Roggendorf; Kristoffer G. van der Zee (Comput. Math. Appl., 2020)

Data-Driven Finite Elements Methods: Machine Learning Acceleration of Goal-Oriented Computations. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (CoRR, 2020)

Discretization of Linear Problems in Banach Spaces: Residual Minimization, Nonlinear Petrov-Galerkin, and Monotone Mixed Methods. - Ignacio Muga; Kristoffer G. van der Zee (SIAM J. Numer. Anal., 2020)

A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (Comput. Math. Appl., 2021)

Linearisation of the Travel Time Functional in Porous Media Flows. - Paul Houston; Connor J. Rourke; Kristoffer G. van der Zee (CoRR, 2021)

Neural Control of Discrete Weak Formulations: Galerkin, Least-Squares and Minimal-Residual Methods with Quasi-Optimal Weights. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (CoRR, 2022)

An editorial perspective: new team, aims and scope and advances of EWCO. - Jessica Zhang 001; John A. Evans; Héctor Gómez; Kris G. van der Zee (Eng. Comput., 2022)

Projection in negative norms and the regularization of rough linear functionals. - Felipe Millar; Ignacio Muga; Sergio Rojas; Kristoffer G. van der Zee (Numerische Mathematik, 2022)

Linearization of the Travel Time Functional in Porous Media Flows. - Paul Houston; Connor J. Rourke; Kristoffer G. van der Zee (SIAM J. Sci. Comput., 2022)

An editorial perspective: recent updates of EWCO and submission guidelines. - Jessica Zhang 001; John A. Evans; Héctor Gómez; Kristoffer G. van der Zee (Eng. Comput., 2023)

Editorial UKACM 2022: advances in computational mechanics. - Jelena Ninic; Kristoffer G. van der Zee; Matteo Icardi; Fangying Wang (Eng. Comput., 2023)

Global-local multidisciplinary optimisation for the evaluation of local constraints on finer meshes in preliminary aircraft design. - Massimo Sferza; Jelena Ninic; Florian Glock; Christoph Hofer; Fernass Daoud; Dimitrios Chronopoulos; Kristoffer G. van der Zee (Eng. Comput., 2023)

Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. - Ignacio Brevis; Ignacio Muga; David Pardo; Oscar A. Rodríguez; Kristoffer G. van der Zee (Comput. Math. Appl., 2024)

A Shape-Newton Method for Free-Boundary Problems Subject to the Bernoulli Boundary Condition. - Yiyun Fan; John Billingham; Kristoffer G. van der Zee (SIAM J. Sci. Comput., 2024)

Neural network methods for power series problems of Perron-Frobenius operators. - T. Udomworarat; Ignacio Brevis; M. Richter; Sergio Rojas; Kristoffer G. van der Zee (CoRR, 2025)