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Journal Articles
- 2024
[j46]Kai Bergermann
, Martin Stoll:
Adaptive Rational Krylov Methods for Exponential Runge-Kutta Integrators. SIAM J. Matrix Anal. Appl. 45(1): 744-770 (2024)- [j45]Christoph Plate, Sebastian Sager, Martin Stoll, Manuel Tetschke:
Second-Order Partial Outer Convexification for Switched Dynamical Systems. IEEE Trans. Autom. Control. 69(7): 4643-4656 (2024) - 2023
- [j44]Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi, Martin Stoll:
An improved penalty algorithm using model order reduction for MIPDECO problems with partial observations. Comput. Optim. Appl. 84(1): 191-223 (2023) - [j43]Kirandeep Kour, Sergey Dolgov, Martin Stoll, Peter Benner:
Efficient Structure-preserving Support Tensor Train Machine. J. Mach. Learn. Res. 24: 4:1-4:22 (2023) - 2022
- [j42]Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi, Martin Stoll:
Improved penalty algorithm for mixed integer PDE constrained optimization problems. Comput. Math. Appl. 116: 2-14 (2022) - 2021
- [j41]Kai Bergermann, Martin Stoll:
Orientations and matrix function-based centralities in multiplex network analysis of urban public transport. Appl. Netw. Sci. 6(1): 90 (2021) - [j40]Dominik Alfke, Martin Stoll:
Pseudoinverse graph convolutional networks. Data Min. Knowl. Discov. 35(4): 1318-1341 (2021) - [j39]David Glickenstein, Keaton Hamm, Xiaoming Huo, Yajun Mei, Martin Stoll:
Editorial: Mathematical Fundamentals of Machine Learning. Frontiers Appl. Math. Stat. 7: 674785 (2021) - [j38]Dominik Bünger, Miriam Gondos, Lucile Peroche, Martin Stoll:
An Empirical Study of Graph-Based Approaches for Semi-supervised Time Series Classification. Frontiers Appl. Math. Stat. 7: 784855 (2021) - [j37]Alexandra Bünger, Valeria Simoncini, Martin Stoll:
A Low-Rank Matrix Equation Method for Solving PDE-Constrained Optimization Problems. SIAM J. Sci. Comput. 43(5): S637-S654 (2021) - [j36]Kai Bergermann, Martin Stoll, Toni Volkmer:
Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products. SIAM J. Math. Data Sci. 3(2): 758-785 (2021) - 2020
- [j35]Yue Qiu, Sara Grundel, Martin Stoll, Peter Benner:
Efficient numerical methods for gas network modeling and simulation. Networks Heterog. Media 15(4): 653-679 (2020) - [j34]John W. Pearson, Margherita Porcelli, Martin Stoll:
Interior-point methods and preconditioning for PDE-constrained optimization problems involving sparsity terms. Numer. Linear Algebra Appl. 27(2) (2020) - [j33]Alexandra Bünger, Sergey Dolgov, Martin Stoll:
A Low-Rank Tensor Method for PDE-Constrained Optimization with Isogeometric Analysis. SIAM J. Sci. Comput. 42(1): A140-A161 (2020) - 2019
- [j32]Roland Herzog, John W. Pearson, Martin Stoll:
Fast iterative solvers for an optimal transport problem. Adv. Comput. Math. 45(2): 495-517 (2019) - [j31]Peter Benner, Akwum Onwunta, Martin Stoll:
A Low-Rank Inexact Newton-Krylov Method for Stochastic Eigenvalue Problems. Comput. Methods Appl. Math. 19(1): 5-22 (2019) - 2018
- [j30]Wei Zhao, Y. C. Hon, Martin Stoll:
Numerical simulations of nonlocal phase-field and hyperbolic nonlocal phase-field models via localized radial basis functions-based pseudo-spectral method (LRBF-PSM). Appl. Math. Comput. 337: 514-534 (2018) - [j29]Wei Zhao, Yiu-chung Hon, Martin Stoll:
Localized radial basis functions-based pseudo-spectral method (LRBF-PSM) for nonlocal diffusion problems. Comput. Math. Appl. 75(5): 1685-1704 (2018) - [j28]Dominik Alfke, Daniel Potts, Martin Stoll, Toni Volkmer:
NFFT Meets Krylov Methods: Fast Matrix-Vector Products for the Graph Laplacian of Fully Connected Networks. Frontiers Appl. Math. Stat. 4: 61 (2018) - [j27]Peter Benner, Yue Qiu, Martin Stoll:
Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 6(2): 965-989 (2018) - [j26]Jessica Bosch, Steffen Klamt, Martin Stoll:
Generalizing Diffuse Interface Methods on Graphs: Nonsmooth Potentials and Hypergraphs. SIAM J. Appl. Math. 78(3): 1350-1377 (2018) - 2017
- [j25]Margherita Porcelli, Valeria Simoncini, Martin Stoll:
Preconditioning PDE-constrained optimization with L1-sparsity and control constraints. Comput. Math. Appl. 74(5): 1059-1075 (2017) - [j24]Sergey Dolgov, Martin Stoll:
Low-Rank Solution to an Optimization Problem Constrained by the Navier-Stokes Equations. SIAM J. Sci. Comput. 39(1) (2017) - 2016
- [j23]Sergey Dolgov, John W. Pearson, Dmitry V. Savostyanov, Martin Stoll:
Fast tensor product solvers for optimization problems with fractional differential equations as constraints. Appl. Math. Comput. 273: 604-623 (2016) - [j22]Martin Stoll, John W. Pearson, Philip K. Maini:
Fast solvers for optimal control problems from pattern formation. J. Comput. Phys. 304: 27-45 (2016) - [j21]Peter Benner, Akwum Onwunta, Martin Stoll:
Block-Diagonal Preconditioning for Optimal Control Problems Constrained by PDEs with Uncertain Inputs. SIAM J. Matrix Anal. Appl. 37(2): 491-518 (2016) - 2015
- [j20]Hamdullah Yücel, Martin Stoll, Peter Benner:
A discontinuous Galerkin method for optimal control problems governed by a system of convection-diffusion PDEs with nonlinear reaction terms. Comput. Math. Appl. 70(10): 2414-2431 (2015) - [j19]Andrew T. Barker, Martin Stoll:
Domain decomposition in time for PDE-constrained optimization. Comput. Phys. Commun. 197: 136-143 (2015) - [j18]Peter Benner, Akwum Onwunta, Martin Stoll:
Low-Rank Solution of Unsteady Diffusion Equations with Stochastic Coefficients. SIAM/ASA J. Uncertain. Quantification 3(1): 622-649 (2015) - [j17]Jessica Bosch, Martin Stoll:
A Fractional Inpainting Model Based on the Vector-Valued Cahn-Hilliard Equation. SIAM J. Imaging Sci. 8(4): 2352-2382 (2015) - [j16]Martin Stoll, Tobias Breiten:
A Low-Rank in Time Approach to PDE-Constrained Optimization. SIAM J. Sci. Comput. 37(1) (2015) - [j15]Jessica Bosch, Martin Stoll:
Preconditioning for Vector-Valued Cahn-Hilliard Equations. SIAM J. Sci. Comput. 37(5) (2015) - 2014
- [j14]Jessica Bosch, Martin Stoll, Peter Benner:
Fast solution of Cahn-Hilliard variational inequalities using implicit time discretization and finite elements. J. Comput. Phys. 262: 38-57 (2014) - [j13]John W. Pearson, Martin Stoll, Andrew J. Wathen:
Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function. Numer. Linear Algebra Appl. 21(1): 81-97 (2014) - [j12]Jessica Bosch, David Kay, Martin Stoll, Andrew J. Wathen:
Fast Solvers for Cahn-Hilliard Inpainting. SIAM J. Imaging Sci. 7(1): 67-97 (2014) - 2013
- [j11]Hamdullah Yücel, Martin Stoll, Peter Benner:
Discontinuous Galerkin finite element methods with shock-capturing for nonlinear convection dominated models. Comput. Chem. Eng. 58: 278-287 (2013) - [j10]Martin Stoll, Andy J. Wathen:
All-at-once solution of time-dependent Stokes control. J. Comput. Phys. 232(1): 498-515 (2013) - [j9]Peter Benner, Jens Saak, Martin Stoll, Heiko K. Weichelt:
Efficient Solution of Large-Scale Saddle Point Systems Arising in Riccati-Based Boundary Feedback Stabilization of Incompressible Stokes Flow. SIAM J. Sci. Comput. 35(5) (2013) - [j8]John W. Pearson, Martin Stoll:
Fast Iterative Solution of Reaction-Diffusion Control Problems Arising from Chemical Processes. SIAM J. Sci. Comput. 35(5) (2013) - 2012
- [j7]Luise Blank, Lavinia Sarbu, Martin Stoll:
Preconditioning for Allen-Cahn variational inequalities with non-local constraints. J. Comput. Phys. 231(16): 5406-5420 (2012) - [j6]Martin Stoll, Andy J. Wathen:
Preconditioning for partial differential equation constrained optimization with control constraints. Numer. Linear Algebra Appl. 19(1): 53-71 (2012) - [j5]John W. Pearson, Martin Stoll, Andrew J. Wathen:
Regularization-Robust Preconditioners for Time-Dependent PDE-Constrained Optimization Problems. SIAM J. Matrix Anal. Appl. 33(4): 1126-1152 (2012) - 2010
- [j4]Tyrone Rees, Martin Stoll, Andy J. Wathen:
All-at-once preconditioning in PDE-constrained optimization. Kybernetika 46(2): 341-360 (2010) - [j3]Tyrone Rees, Martin Stoll:
Block-triangular preconditioners for PDE-constrained optimization. Numer. Linear Algebra Appl. 17(6): 977-996 (2010) - [j2]H. Sue Dollar, Nicholas I. M. Gould, Martin Stoll, Andrew J. Wathen:
Preconditioning Saddle-Point Systems with Applications in Optimization. SIAM J. Sci. Comput. 32(1): 249-270 (2010) - 2008
- [j1]Martin Stoll, Andy J. Wathen:
Combination Preconditioning and the Bramble-Pasciak+ Preconditioner. SIAM J. Matrix Anal. Appl. 30(2): 582-608 (2008)
Conference and Workshop Papers
- 2024
- [c5]Marcel Hallgarten, Ismail Kisa, Martin Stoll, Andreas Zell:
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction. IV 2024: 795-802 - 2023
- [c4]Marcel Hallgarten, Martin Stoll, Andreas Zell:
From Prediction to Planning With Goal Conditioned Lane Graph Traversals. ITSC 2023: 951-958 - 2022
- [c3]Yousef Alnaser, Jan Langer, Martin Stoll:
Accelerating Kernel Ridge Regression with Conjugate Gradient Method for large-scale data using FPGA High-level Synthesis. H2RC@SC 2022: 28-36 - 2019
- [c2]Pedro Mercado, Jessica Bosch, Martin Stoll:
Node Classification for Signed Social Networks Using Diffuse Interface Methods. ECML/PKDD (1) 2019: 524-540 - 2013
- [c1]Peter Benner, Jens Saak, Martin Stoll, Heiko K. Weichelt:
Efficient Solvers for Large-Scale Saddle Point Systems Arising in Feedback Stabilization of Multi-field Flow Problems. System Modelling and Optimization 2013: 11-20
Informal and Other Publications
- 2024
- [i35]Min-Li Zeng, Martin Stoll:
A splitting-based KPIK method for eddy current optimal control problems in an all-at-once approach. CoRR abs/2403.11611 (2024) - [i34]Marcel Hallgarten, Julián Zapata, Martin Stoll, Katrin Renz, Andreas Zell:
Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios? CoRR abs/2404.07569 (2024) - [i33]Theresa Wagner, Franziska Nestler, Martin Stoll:
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives. CoRR abs/2404.17344 (2024) - [i32]Alexandra Bünger, Tom-Christian Riemer, Martin Stoll:
IETI-based Low-Rank method for PDE-constrained optimization. CoRR abs/2405.06458 (2024) - [i31]Kai Bergermann, Martin Stoll:
Gradient flow-based modularity maximization for community detection in multiplex networks. CoRR abs/2408.15003 (2024) - 2023
- [i30]Marcel Hallgarten, Martin Stoll, Andreas Zell:
From Prediction to Planning With Goal Conditioned Lane Graph Traversals. CoRR abs/2302.07753 (2023) - [i29]Kirandeep Kour, Sergey Dolgov, Peter Benner, Martin Stoll, Max Pfeffer:
A weighted subspace exponential kernel for support tensor machines. CoRR abs/2302.08134 (2023) - [i28]Kai Bergermann, Martin Stoll:
Adaptive rational Krylov methods for exponential Runge-Kutta integrators. CoRR abs/2303.09482 (2023) - [i27]Martin Stoll, Markus Mazzola, Maxim Dolgov, Jürgen Mathes, Nicolas Möser:
Scaling Planning for Automated Driving using Simplistic Synthetic Data. CoRR abs/2305.18942 (2023) - [i26]Marcel Hallgarten, Ismail Kisa, Martin Stoll, Andreas Zell:
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction. CoRR abs/2306.00605 (2023) - [i25]Alexandra Bünger, Roland Herzog, Andreas Naumann, Martin Stoll:
Uncertainty Propagation of Initial Conditions in Thermal Models. CoRR abs/2306.12736 (2023) - [i24]Steffen Hagedorn, Marcel Hallgarten, Martin Stoll, Alexandru Condurache:
Rethinking Integration of Prediction and Planning in Deep Learning-Based Automated Driving Systems: A Review. CoRR abs/2308.05731 (2023) - [i23]Kai Bergermann, Martin Stoll, Francesco Tudisco:
A nonlinear spectral core-periphery detection method for multiplex networks. CoRR abs/2310.19697 (2023) - [i22]Theresa Wagner, John W. Pearson, Martin Stoll:
A Preconditioned Interior Point Method for Support Vector Machines Using an ANOVA-Decomposition and NFFT-Based Matrix-Vector Products. CoRR abs/2312.00538 (2023) - 2022
- [i21]Kai Bergermann, Carsten Deibel, Roland Herzog, Roderick C. I. MacKenzie, Jan-Frederik Pietschmann, Martin Stoll:
Preconditioning for a Phase-Field Model with Application to Morphology Evolution in Organic Semiconductors. CoRR abs/2204.03575 (2022) - [i20]Jan Blechschmidt, Jan-Frederik Pietschmann, Tom-Christian Riemer, Martin Stoll, Max Winkler:
A comparison of PINN approaches for drift-diffusion equations on metric graphs. CoRR abs/2205.07195 (2022) - [i19]Edgar Ivan Sanchez Medina, Steffen Linke, Martin Stoll, Kai Sundmacher:
Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution. CoRR abs/2212.01199 (2022) - 2021
- [i18]Dominik Alfke, Miriam Gondos, Lucile Peroche, Martin Stoll:
A Study of Graph-Based Approaches for Semi-Supervised Time Series Classification. CoRR abs/2104.08153 (2021) - [i17]Kai Bergermann, Martin Stoll:
Matrix function-based centrality measures for layer-coupled multiplex networks. CoRR abs/2104.14368 (2021) - [i16]Kai Bergermann, Martin Stoll:
Orientations and matrix function-based centralities in multiplex network analysis of urban public transport. CoRR abs/2107.12695 (2021) - [i15]Alexandra Bünger, Martin Stoll:
A low-rank tensor method to reconstruct sparse initial states for PDEs with Isogeometric Analysis. CoRR abs/2109.03119 (2021) - [i14]Anahita Iravanizad, Edgar Ivan Sanchez Medina, Martin Stoll:
RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs. CoRR abs/2109.07555 (2021) - [i13]Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi, Martin Stoll:
An Improved Penalty Algorithm using Model Order Reduction for MIPDECO problems with partial observations. CoRR abs/2110.03341 (2021) - [i12]Franziska Nestler, Martin Stoll, Theresa Wagner:
Learning in High-Dimensional Feature Spaces Using ANOVA-Based Fast Matrix-Vector Multiplication. CoRR abs/2111.10140 (2021) - 2020
- [i11]Kirandeep Kour, Sergey Dolgov, Martin Stoll, Peter Benner:
Efficient Structure-preserving Support Tensor Train Machine. CoRR abs/2002.05079 (2020) - [i10]Alexandra Bünger, Valeria Simoncini, Martin Stoll:
A low-rank matrix equation method for solving PDE-constrained optimization problems. CoRR abs/2005.14499 (2020) - [i9]Kai Bergermann, Martin Stoll, Toni Volkmer:
Semi-supervised Learning for Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix Vector Products. CoRR abs/2007.05239 (2020) - [i8]Dominik Alfke, Martin Stoll:
Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs. CoRR abs/2008.00720 (2020) - 2019
- [i7]Dominik Alfke, Martin Stoll:
Semi-Supervised Classification on Non-Sparse Graphs Using Low-Rank Graph Convolutional Networks. CoRR abs/1905.10224 (2019) - [i6]Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi, Martin Stoll:
Improved Penalty Algorithm for Mixed Integer PDE Constrained Optimization (MIPDECO) Problems. CoRR abs/1907.06462 (2019) - [i5]Martin Stoll, Max Winkler:
Optimization of a partial differential equation on a complex network. CoRR abs/1907.07806 (2019) - [i4]Tobias Breiten, Sergey Dolgov, Martin Stoll:
Solving differential Riccati equations: A nonlinear space-time method using tensor trains. CoRR abs/1912.06944 (2019) - [i3]Martin Stoll:
A literature survey of matrix methods for data science. CoRR abs/1912.07896 (2019) - 2018
- [i2]Dominik Alfke, Daniel Potts, Martin Stoll, Toni Volkmer:
NFFT meets Krylov methods: Fast matrix-vector products for the graph Laplacian of fully connected networks. CoRR abs/1808.04580 (2018) - [i1]Jessica Bosch, Pedro Mercado, Martin Stoll:
Node classification for signed networks using diffuse interface methods. CoRR abs/1809.06432 (2018)
Coauthor Index
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