Michael Feischl

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 31

Top Topics

Weighting Factor

Recurrent Neural Networks

Mesh Refinement

Top Venues

SIAM J. Numer. Anal.

Numerische Mathematik

Comput. Methods Appl. Math.

Publications

Michael Feischl, Dirk Praetorius, Michele Ruggeri
Computational Methods in Applied Mathematics (CMAM 2022 Conference, Part 2). Comput. Methods Appl. Math. 24 (3) (2024)
Michael Feischl, Hubert Hackl
Adaptive Image Compression via Optimal Mesh Refinement. Comput. Methods Appl. Math. 24 (2) (2024)
Michael Feischl, Alexander Rieder, Fabian Zehetgruber
Towards optimal hierarchical training of neural networks. CoRR (2024)
Michael Feischl, Dirk Praetorius, Michele Ruggeri
Computational Methods in Applied Mathematics (CMAM 2022 Conference, Part 1). Comput. Methods Appl. Math. 24 (2) (2024)
Michael Feischl, Caroline Lasser, Christian Lubich, Jörg Nick
Regularized dynamical parametric approximation. CoRR (2024)
Xin An, Josef Dick, Michael Feischl, Andrea Scaglioni, Thanh Tran
Sparse grid approximation of the stochastic Landau-Lifshitz-Gilbert equation. CoRR (2023)
Jan Bohn, Michael Feischl, Balázs Kovács
FEM-BEM Coupling for the Maxwell-Landau-Lifshitz-Gilbert Equations via Convolution Quadrature: Weak Form and Numerical Approximation. Comput. Methods Appl. Math. 23 (1) (2023)
Michael Feischl, Hubert Hackl
Adaptive Image Compression via Optimal Mesh Refinement. CoRR (2023)
Jan Bohn, Willy Dörfler, Michael Feischl, Stefan Karch
Adaptive mesh refinement for the Landau-Lifshitz-Gilbert equation. CoRR (2023)
Philipp Bringmann, Michael Feischl, Ani Miraçi, Dirk Praetorius, Julian Streitberger
On full linear convergence and optimal complexity of adaptive FEM with inexact solver. CoRR (2023)
Michael Feischl
Inf-sup stability implies quasi-orthogonality. Math. Comput. 91 (337) (2022)
Georgios Akrivis, Michael Feischl, Balázs Kovács, Christian Lubich
Higher-order linearly implicit full discretization of the Landau-Lifshitz-Gilbert equation. Math. Comput. 90 (329) (2021)
Michael Feischl, Andrea Scaglioni
Convergence of adaptive stochastic collocation with finite elements. Comput. Math. Appl. 98 (2021)
Josef Dick, Michael Feischl
A quasi-Monte Carlo data compression algorithm for machine learning. J. Complex. 67 (2021)
Jan Bohn, Michael Feischl
Recurrent neural networks as optimal mesh refinement strategies. Comput. Math. Appl. 97 (2021)
Michael Feischl, Christoph Schwab
-FEM for Gevrey regularity with isotropic singularities. Numerische Mathematik 144 (2) (2020)
Michael Feischl, Andrea Scaglioni
Convergence of adaptive stochastic collocation with finite elements. CoRR (2020)
Josef Dick, Michael Feischl
A quasi-Monte Carlo data compression algorithm for machine learning. CoRR (2020)
Michael Feischl, Daniel Peterseim
Sparse Compression of Expected Solution Operators. SIAM J. Numer. Anal. 58 (6) (2020)
Michael Feischl
Inf-sup stability implies quasi-orthogonality. CoRR (2020)
Jan Bohn, Michael Feischl
Recurrent Neural Networks as Optimal Mesh Refinement Strategies. CoRR (2019)
Michael Feischl, Frances Y. Kuo, Ian H. Sloan
-matrices. Numerische Mathematik 142 (3) (2019)
Josef Dick, Michael Feischl, Christoph Schwab
Improved Efficiency of a Multi-Index FEM for Computational Uncertainty Quantification. SIAM J. Numer. Anal. 57 (4) (2019)
Michael Feischl
Optimality of a Standard Adaptive Finite Element Method for the Stokes Problem. SIAM J. Numer. Anal. 57 (3) (2019)
Michael Feischl, Frances Y. Kuo, Ian H. Sloan
-matrices. Numerische Mathematik 140 (3) (2018)
Markus Aurada, Michael Feischl, Thomas Führer, Michael Karkulik, Jens Markus Melenk, Dirk Praetorius
Local inverse estimates for non-local boundary integral operators. Math. Comput. 86 (308) (2017)
Michael Feischl, Thanh Tran
Existence of Regular Solutions of the Landau-Lifshitz-Gilbert Equation in 3D with Natural Boundary Conditions. SIAM J. Math. Anal. 49 (6) (2017)
Michael Feischl, Gregor Gantner, Alexander Haberl, Dirk Praetorius
Optimal convergence for adaptive IGA boundary element methods for weakly-singular integral equations. Numerische Mathematik 136 (1) (2017)
Michael Feischl, Thanh Tran
The Eddy Current-LLG Equations: FEM-BEM Coupling and A Priori Error Estimates. SIAM J. Numer. Anal. 55 (4) (2017)
Michael Feischl, Gregor Gantner, Alexander Haberl, Dirk Praetorius, Thomas Führer
Adaptive boundary element methods for optimal convergence of point errors. Numerische Mathematik 132 (3) (2016)
Michael Feischl, Dirk Praetorius, Kristoffer G. van der Zee
An Abstract Analysis of Optimal Goal-Oriented Adaptivity. SIAM J. Numer. Anal. 54 (3) (2016)
Michael Feischl, Thomas Führer, Michael Karkulik, Dirk Praetorius
Stability of symmetric and nonsymmetric FEM-BEM couplings for nonlinear elasticity problems. Numerische Mathematik 130 (2) (2015)
Michael Feischl, Thomas Führer, Dirk Praetorius
Adaptive FEM with Optimal Convergence Rates for a Certain Class of Nonsymmetric and Possibly Nonlinear Problems. SIAM J. Numer. Anal. 52 (2) (2014)
Michael Feischl, Marcus Page, Dirk Praetorius
Convergence and quasi-optimality of adaptive FEM with inhomogeneous Dirichlet data. J. Comput. Appl. Math. 255 (2014)
Michael Feischl, Thomas Führer, Gregor Mitscha-Eibl, Dirk Praetorius, Ernst P. Stephan
Convergence of Adaptive BEM and Adaptive FEM-BEM Coupling for Estimators Without h-Weighting Factor. Comput. Methods Appl. Math. 14 (4) (2014)
Carsten Carstensen, Michael Feischl, Marcus Page, Dirk Praetorius
Axioms of adaptivity. Comput. Math. Appl. 67 (6) (2014)
Markus Aurada, Michael Ebner, Michael Feischl, Samuel Ferraz-Leite, Thomas Führer, Petra Goldenits, Michael Karkulik, Markus Mayr, Dirk Praetorius
HILBERT - a MATLAB implementation of adaptive 2D-BEM - HILBERT Is a Lovely Boundary Element Research Tool. Numer. Algorithms 67 (1) (2014)
Markus Aurada, Michael Feischl, Thomas Führer, Michael Karkulik, Dirk Praetorius
Efficiency and Optimality of Some Weighted-Residual Error Estimator for Adaptive 2D Boundary Element Methods. Comput. Methods Appl. Math. 13 (3) (2013)
Michael Feischl, Michael Karkulik, Jens Markus Melenk, Dirk Praetorius
Quasi-optimal Convergence Rate for an Adaptive Boundary Element Method. SIAM J. Numer. Anal. 51 (2) (2013)