Application of modal filtering to a spectral difference method. - Jan Glaubitz; Philipp Öffner; Thomas Sonar (Math. Comput., 2018)

Shock capturing by Bernstein polynomials for scalar conservation laws. - Jan Glaubitz (Appl. Math. Comput., 2019)

Smooth and Compactly Supported Viscous Sub-cell Shock Capturing for Discontinuous Galerkin Methods. - Jan Glaubitz; Alberto Costa Nogueira Jr.; João Lucas de Sousa Almeida; R. F. Cantão; C. A. C. Silva (J. Sci. Comput., 2019)

High Order Edge Sensors with ℓ1 Regularization for Enhanced Discontinuous Galerkin Methods. - Jan Glaubitz; Anne Gelb (SIAM J. Sci. Comput., 2019)

Stable discretisations of high-order discontinuous Galerkin methods on equidistant and scattered points. - Jan Glaubitz; Philipp Öffner (CoRR, 2020)

Constructing Positive Interpolatory Cubature Formulas. - Jan Glaubitz (CoRR, 2020)

Stable High Order Quadrature Rules for Scattered Data and General Weight Functions. - Jan Glaubitz (SIAM J. Numer. Anal., 2020)

Towards stable radial basis function methods for linear advection problems. - Jan Glaubitz; Élise Le Mélédo; Philipp Öffner (Comput. Math. Appl., 2021)

Construction and application of provable positive and exact cubature formulas. - Jan Glaubitz (CoRR, 2021)

Towards stability of radial basis function based cubature formulas. - Jan Glaubitz; Jonah A. Reeger (CoRR, 2021)

Stable high-order cubature formulas for experimental data. - Jan Glaubitz (J. Comput. Phys., 2021)

Stabilizing Radial Basis Function Methods for Conservation Laws Using Weakly Enforced Boundary Conditions. - Jan Glaubitz; Anne Gelb (J. Sci. Comput., 2021)

Sequential Image Recovery from Noisy and Under-Sampled Fourier Data. - Yao Xiao; Jan Glaubitz; Anne Gelb; Guohui Song (J. Sci. Comput., 2022)

Towards stability results for global radial basis function based quadrature formulas. - Jan Glaubitz; Jonah A. Reeger (CoRR, 2023)

High-order upwind summation-by-parts methods for nonlinear conservation laws. - Hendrik Ranocha; Andrew R. Winters; Michael Schlottke-Lakemper; Philipp Öffner; Jan Glaubitz; Gregor J. Gassner (CoRR, 2023)

Generalized Sparse Bayesian Learning and Application to Image Reconstruction. - Jan Glaubitz; Anne Gelb; Guohui Song (SIAM/ASA J. Uncertain. Quantification, 2023)

Summation-by-Parts Operators for General Function Spaces. - Jan Glaubitz; Jan Nordström; Philipp Öffner (SIAM J. Numer. Anal., 2023)

Sequential Image Recovery Using Joint Hierarchical Bayesian Learning. - Yao Xiao; Jan Glaubitz (J. Sci. Comput., 2023)

Multi-dimensional summation-by-parts operators for general function spaces: Theory and construction. - Jan Glaubitz; Simon-Christian Klein; Jan Nordström; Philipp Öffner (J. Comput. Phys., 2023)

Generalized sparsity-promoting solvers for Bayesian inverse problems: Versatile sparsifying transforms and unknown noise variances. - Jonathan Lindbloom; Jan Glaubitz; Anne Gelb (CoRR, 2024)

An optimization-based construction procedure for function space based summation-by-parts operators on arbitrary grids. - Jan Glaubitz; Jan Nordström; Philipp Öffner (CoRR, 2024)

Summation-by-parts operators for general function spaces: The second derivative. - Jan Glaubitz; Simon-Christian Klein; Jan Nordström; Philipp Öffner (J. Comput. Phys., 2024)

Leveraging Joint Sparsity in Hierarchical Bayesian Learning. - Jan Glaubitz; Anne Gelb (SIAM/ASA J. Uncertain. Quantification, 2024)

Energy-Stable Global Radial Basis Function Methods on Summation-By-Parts Form. - Jan Glaubitz; Jan Nordström; Philipp Öffner (J. Sci. Comput., 2024)

Generalized upwind summation-by-parts operators and their application to nodal discontinuous Galerkin methods. - Jan Glaubitz; Hendrik Ranocha; Andrew R. Winters; Michael Schlottke-Lakemper; Philipp Öffner; Gregor Gassner (J. Comput. Phys., 2025)

On the robustness of high-order upwind summation-by-parts methods for nonlinear conservation laws. - Hendrik Ranocha; Andrew R. Winters; Michael Schlottke-Lakemper; Philipp Öffner; Jan Glaubitz; Gregor J. Gassner (J. Comput. Phys., 2025)

Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems. - Jonathan Lindbloom; Mirjeta Pasha; Jan Glaubitz; Youssef Marzouk 001 (CoRR, 2025)

Efficient sampling for sparse Bayesian learning using hierarchical prior normalization. - Jan Glaubitz; Youssef Marzouk 001 (CoRR, 2025)