activity
20122026
most citedMassively parallel solvers for elliptic PDEs in Numerical Weather- and Climate Prediction

79 citations · 258 across the 61 of their papers we have counts for

collaborators

72 papers

math.NA2026

Efficient localised model reduction for multiscale PDEs via Grassmannian interpolation

Christian Alber, Markus Bachmayr, Robert Scheichl +1

Multiscale, parameter-dependent partial differential equations (PDEs) pose severe computational challenges due to strong coefficient heterogeneity and high-dimensional parameter sp…

math.ST2026

Fast-Mixing Markov Chains without Gradients

Robert Kutri, Robert Scheichl

Most approaches for accelerating Markov chain mixing either rely on incorporating expensive geometric information in the proposals, or reduce the per-step cost of sampling via surr…

math.NA2025

Robust spectral preconditioning for high-Péclet number convection-diffusion

Lukas Holbach, Peter Bastian, Robert Scheichl

We introduce a two-level hybrid restricted additive Schwarz (RAS) preconditioner for heterogeneous steady-state convection-diffusion equations at high Péclet numbers. Our construct…

math.NA2025

Optimal Spectral Approximation in the Overlaps for Generalized Finite Element Methods

Christian Alber, Peter Bastian, Moritz Hauck +1

In this paper, we study a generalized finite element method for solving second-order elliptic partial differential equations with rough coefficients. The method uses local approxim…

math.NA2025

A Budgeted Multi-Level Monte Carlo Method for Full Field Estimates of Multi-PDE Problems

Niklas Baumgarten, Robert Kutri, Robert Scheichl

We present a high-performance budgeted multi-level Monte Carlo method for estimates on the entire spatial domain of multi-PDE problems with random input data. The method is designe…

math.AP2025

Statistical parameter identification of mixed-mode patterns from a single experimental snapshot

Alexey Kazarnikov, Robert Scheichl, Irving R. Epstein +2

Parameter identification in pattern formation models from a single experimental snapshot is challenging, as traditional methods often require knowledge of initial conditions or tra…