Research Group Massimo Fornasier
Massimo Fornasier
Prof. Dr.
Core PI
Massimo Fornasier
holds the Chair of Applied Numerical Analysis at TU Munich.
His embraces a broad spectrum of problems in mathematical modeling, analysis and numerical analysis. He is particularly interested in the concept of compression as appearing in different forms in data analysis, image and signal processing, and in the adaptive numerical solutions of partial differential equations or high-dimensional optimization problems.
Team members @MCML
PostDocs
Christian Fiedler
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Xingchao Jian
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Francesco Mattesini
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Tim Roith
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Alessandro Scagliotti
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Viktor Stein
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Lukang Sun
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
Anna Veselovska
Dr.
→ Group Massimo Fornasier
Applied Numerical Analysis
PhD Students
Apostolos Evangelidis
→ Group Massimo Fornasier
Applied Numerical Analysis
Jona Klemenc
→ Group Massimo Fornasier
Applied Numerical Analysis
Hannah Laus
→ Group Massimo Fornasier
Applied Numerical Analysis
Recent News @MCML
Publications @MCML
2026
[69]
A. Evangelidis • F. Krahmer
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL
[68]
V. Stein • J. M. de Frutos
Approximating f -Divergences with Rank Statistics.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
Approximating f -Divergences with Rank Statistics.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
[67]
V. Stein • J. M. de Frutos
Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub
[66]
X. Sun • A. Jordana • M. Fornasier • J. Etesami • M. Khadiv
Consensus-based Optimization (CBO) for trajectory optimization in Robotics.
FOR @ICRA 2026 - 2nd Workshop on Frontiers of Optimization for Robotics at the IEEE International Conference on Robotics and Automation. Vienna, Austria, Jun 01-05, 2026. URL
Consensus-based Optimization (CBO) for trajectory optimization in Robotics.
FOR @ICRA 2026 - 2nd Workshop on Frontiers of Optimization for Robotics at the IEEE International Conference on Robotics and Automation. Vienna, Austria, Jun 01-05, 2026. URL
[65]
A. Scagliotti • F. Scagliotti • L. Locati • F. Sottotetti
Ensemble optimal control for managing drug resistance in cancer therapies.
Bulletin of Mathematical Biology 88.92. May. 2026. DOI
Ensemble optimal control for managing drug resistance in cancer therapies.
Bulletin of Mathematical Biology 88.92. May. 2026. DOI
[64]
F. Colasanto • M. Focardi • M. Fornasier • F. Mattesini
Sharp Rates of MMD Empirical Estimation with Power Kernels.
Preprint (May. 2026). arXiv
Sharp Rates of MMD Empirical Estimation with Power Kernels.
Preprint (May. 2026). arXiv
[63]
A. Scagliotti • T. M. Surowiec
Risk-Averse Ensemble Control for Control-Affine Systems.
Preprint (May. 2026). arXiv
Risk-Averse Ensemble Control for Control-Affine Systems.
Preprint (May. 2026). arXiv
[62]
C. Datar • T. Kapoor • A. Chandra • Q. Sun • E. L. Bolager • I. Burak • A. Veselovska • M. Fornasier • F. Dietrich
Fast training of accurate physics-informed neural networks without gradient descent.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. Oral Presentation. To be published. Preprint available. arXiv
Fast training of accurate physics-informed neural networks without gradient descent.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. Oral Presentation. To be published. Preprint available. arXiv
[61]
J. Beddrich • E. Chenchene • M. Fornasier • H. Huang • B. Wohlmuth
Constrained consensus-based optimization and numerical heuristics for the few particle regime.
Journal of Global Optimization. Apr. 2026. DOI GitHub
Constrained consensus-based optimization and numerical heuristics for the few particle regime.
Journal of Global Optimization. Apr. 2026. DOI GitHub
[60]
M. Fornasier • H. Huang • J. Klemenc • G. Malaspina
From Consensus-Based Optimization to Evolution Strategies: Proof of Global Convergence.
Preprint (Feb. 2026). arXiv
From Consensus-Based Optimization to Evolution Strategies: Proof of Global Convergence.
Preprint (Feb. 2026). arXiv
[59]
J. Maly • A. Veselovska
Reliable one-bit quantization of bandlimited graph data via single-shot noise shaping.
Preprint (Feb. 2026). arXiv
Reliable one-bit quantization of bandlimited graph data via single-shot noise shaping.
Preprint (Feb. 2026). arXiv
[58]
L. Paul • H. Rauhut • M. Burger • S. Kabri • T. Roith
Allure of Craquelure: A Variational-Generative Approach to Crack Detection in Paintings.
Preprint (Feb. 2026). arXiv
Allure of Craquelure: A Variational-Generative Approach to Crack Detection in Paintings.
Preprint (Feb. 2026). arXiv
[57]
X. Sun • A. Jordana • M. Fornasier • J. Etesami • M. Khadiv
Consensus-based optimization (CBO): Towards Global Optimality in Robotics.
Preprint (Feb. 2026). arXiv
Consensus-based optimization (CBO): Towards Global Optimality in Robotics.
Preprint (Feb. 2026). arXiv
[56]
C. Fiedler
Statistical Learning Theory for Distributional Classification.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI
Statistical Learning Theory for Distributional Classification.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI
[55]
X. Jian • P. Zhang • L. Tian • F. Ji • W. Liang • W. P. Tay • B. Wen • F. Krahmer
Conformal Prediction for Multi-Source Detection on a Network.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI
Conformal Prediction for Multi-Source Detection on a Network.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI
[54]
M. Fornasier • J. Klemenc • A. Scagliotti
Trade-off Invariance Principle for Minimizers of Regularized Functionals.
Journal of Optimization Theory and Applications 208.78. Jan. 2026. DOI
Trade-off Invariance Principle for Minimizers of Regularized Functionals.
Journal of Optimization Theory and Applications 208.78. Jan. 2026. DOI
[53]
2025
[52]
C. Geldhauser • M. Herrmann • D. Janßen
Traveling Phase Interfaces in Viscous Forward–Backward Diffusion Equations.
Journal of Dynamics and Differential Equations.4. Dec. 2025. DOI
Traveling Phase Interfaces in Viscous Forward–Backward Diffusion Equations.
Journal of Dynamics and Differential Equations.4. Dec. 2025. DOI
[51]
M. Mollenhauer • C. Fiedler
Fuk-Nagaev inequality in smooth Banach spaces: Optimum bounds for distributions of heavy-tailed martingales.
Preprint (Dec. 2025). arXiv
Fuk-Nagaev inequality in smooth Banach spaces: Optimum bounds for distributions of heavy-tailed martingales.
Preprint (Dec. 2025). arXiv
[50]
P.-F. Massiani • C. Fiedler • L. Haverbeck • F. Solowjow • S. Trimpe
Kernel conditional tests from learning-theoretic bounds.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL
Kernel conditional tests from learning-theoretic bounds.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL
[49]
C. Fiedler • A. Scagliotti
Towards optimal control of ensembles of discrete-time systems.
Preprint (Nov. 2025). arXiv
Towards optimal control of ensembles of discrete-time systems.
Preprint (Nov. 2025). arXiv
[48]
L. Sacchelli • A. Scagliotti
A case study in ensemble optimal control for Bayesian input design.
Preprint (Nov. 2025). arXiv
A case study in ensemble optimal control for Bayesian input design.
Preprint (Nov. 2025). arXiv
[47]
O. Åström • C. Geldhauser • M. Grillitsch • O. Hall • A. Sopasakis
Enhancing Carbon Emission Reduction Strategies using OCO and ICOS data.
Scientific Reports 15.36297. Oct. 2025. DOI
Enhancing Carbon Emission Reduction Strategies using OCO and ICOS data.
Scientific Reports 15.36297. Oct. 2025. DOI
[46]
M. Fornasier • L. Sun • R. Ward
Large-Time Analysis of the Langevin Dynamics for Energies Fulfilling Polyak-Lojasiewicz Conditions.
Preprint (Oct. 2025). arXiv
Large-Time Analysis of the Langevin Dynamics for Energies Fulfilling Polyak-Lojasiewicz Conditions.
Preprint (Oct. 2025). arXiv
[45]
C. Fiedler • S. Trimpe
On the Analysis of Suboptimal Nonlinear Model Predictive Control Schemes Without Terminal Constraints.
IEEE Control Systems Letters 9. Sep. 2025. DOI
On the Analysis of Suboptimal Nonlinear Model Predictive Control Schemes Without Terminal Constraints.
IEEE Control Systems Letters 9. Sep. 2025. DOI
[44]
A. Scagliotti • S. Farinelli
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
Nonlinear Analysis 257.113811. Aug. 2025. DOI
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
Nonlinear Analysis 257.113811. Aug. 2025. DOI
[43]
A. Veselovska • J. Prestin
Super-resolution via Prony-Type Polynomials.
SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. DOI
Super-resolution via Prony-Type Polynomials.
SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. DOI
[42]
A. Scagliotti • S. Farinelli
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
VC 2025 - 16th Viennese Conference on Optimal Control and Dynamic Games. Vienna, Austria, Jul 15-18, 2025. PDF
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
VC 2025 - 16th Viennese Conference on Optimal Control and Dynamic Games. Vienna, Austria, Jul 15-18, 2025. PDF
[41]
S. Karnik • A. Veselovska • M. Iwen • F. Krahmer
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL
[40]
E. Pozzoli • A. Scagliotti
Approximation of diffeomorphisms for quantum state transfers.
IEEE Control Systems Letters Early Access. Jun. 2025. DOI
Approximation of diffeomorphisms for quantum state transfers.
IEEE Control Systems Letters Early Access. Jun. 2025. DOI
[39]
K. Jin • J. Latz • C. Liu • A. Scagliotti
Losing momentum in continuous-time stochastic optimisation.
Journal of Machine Learning Research 26.148. Jun. 2025. URL
Losing momentum in continuous-time stochastic optimisation.
Journal of Machine Learning Research 26.148. Jun. 2025. URL
[38]
M. Rauscher • A. Scagliotti • F. Pagginelli Patricio
Shortest-path recovery from signature with an optimal control approach.
Mathematics of Control, Signals, and Systems 37. Jun. 2025. DOI
Shortest-path recovery from signature with an optimal control approach.
Mathematics of Control, Signals, and Systems 37. Jun. 2025. DOI
[37]
S. Almi • M. Fornasier • J. Klemenc • A. Scagliotti
Balanced quasistatic evolutions of critical points in metric spaces.
Preprint (Jun. 2025). arXiv
Balanced quasistatic evolutions of critical points in metric spaces.
Preprint (Jun. 2025). arXiv
[36]
C. Cipriani • M. Fornasier • A. Scagliotti
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI
[35]
M. Fornasier • P. Richtárik • K. Riedl • L. Sun
Consensus-Based Optimization with Truncated Noise.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI
Consensus-Based Optimization with Truncated Noise.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI
[34]
M. Fornasier • P. Heid • G. E. Sodini
Approximation Theory, Computing, and Deep Learning on the Wasserstein Space.
Mathematical Models and Methods in Applied Sciences 34.4. Apr. 2025. DOI
Approximation Theory, Computing, and Deep Learning on the Wasserstein Space.
Mathematical Models and Methods in Applied Sciences 34.4. Apr. 2025. DOI
[33]
L. Sun
Well-posedness and L1−Lp Smoothing Effect of the Porous Media Equation under Poincaré Inequality.
Preprint (Apr. 2025). arXiv
Well-posedness and L1−Lp Smoothing Effect of the Porous Media Equation under Poincaré Inequality.
Preprint (Apr. 2025). arXiv
[32]
F. Krahmer • A. Veselovska
The mathematics of dots and pixels: On the theoretical foundations of image halftoning.
GAMM Mitteilungen 48.1. Mar. 2025. DOI
The mathematics of dots and pixels: On the theoretical foundations of image halftoning.
GAMM Mitteilungen 48.1. Mar. 2025. DOI
[31]
M. Herold • J. S. Jehle • F. Krahmer • A. Veselovska
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis.
International Journal for Uncertainty Quantification 15.4. Mar. 2025. DOI
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis.
International Journal for Uncertainty Quantification 15.4. Mar. 2025. DOI
[30]
M. Fornasier • L. Sun
A PDE Framework of Consensus-Based Optimization for Objectives with Multiple Global Minimizers.
Communications in Partial Differential Equations 50.4. Feb. 2025. DOI
A PDE Framework of Consensus-Based Optimization for Objectives with Multiple Global Minimizers.
Communications in Partial Differential Equations 50.4. Feb. 2025. DOI
[29]
M. Fornasier • L. Sun
Regularity and positivity of solutions of the Consensus-Based Optimization equation: unconditional global convergence.
Preprint (Feb. 2025). arXiv
Regularity and positivity of solutions of the Consensus-Based Optimization equation: unconditional global convergence.
Preprint (Feb. 2025). arXiv
[28]
H. Laus • S. Parkinson • V. Charisopoulos • F. Krahmer • R. Willett
Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay.
Preprint (Feb. 2025). arXiv
Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay.
Preprint (Feb. 2025). arXiv
[27]
M. Fornasier • J. Klemenc • A. Scagliotti
Trade-off Invariance Principle for minimizers of regularized functionals.
Math4AiMl 2025 - 3rd Workshop of UMI Group Mathematics for Artificial Intelligence and Machine Learning. Bari, Italy, Jan 29-31, 2025. arXiv PDF
Trade-off Invariance Principle for minimizers of regularized functionals.
Math4AiMl 2025 - 3rd Workshop of UMI Group Mathematics for Artificial Intelligence and Machine Learning. Bari, Italy, Jan 29-31, 2025. arXiv PDF
[26]
A. Scagliotti
Minimax Problems for Ensembles of Control-Affine Systems.
SIAM Journal on Control and Optimization 63.1. Jan. 2025. DOI
Minimax Problems for Ensembles of Control-Affine Systems.
SIAM Journal on Control and Optimization 63.1. Jan. 2025. DOI
2024
[25]
A. Bonfanti • G. Bruno • C. Cipriani
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI
[24]
F. Hoppe • C. M. Verdun • H. Laus • F. Krahmer • H. Rauhut
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI
[23]
C. Geldhauser • C. Kuehn
Travelling waves for discrete stochastic bistable equations.
Partial Differential Equations and Applications 5.35. Nov. 2024. DOI
Travelling waves for discrete stochastic bistable equations.
Partial Differential Equations and Applications 5.35. Nov. 2024. DOI
[22]
F. Hoppe • C. M. Verdun • H. Laus • S. Endt • M. I. Menzel • F. Krahmer • H. Rauhut
Imaging with Confidence: Uncertainty Quantification for High-dimensional Undersampled MR Images.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub
Imaging with Confidence: Uncertainty Quantification for High-dimensional Undersampled MR Images.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub
[21]
K. Riedl
Mathematical Foundations of Interacting Multi-Particle Systems for Optimization.
Dissertation TU München. Sep. 2024. URL
Mathematical Foundations of Interacting Multi-Particle Systems for Optimization.
Dissertation TU München. Sep. 2024. URL
[20]
C. Geldhauser • K. Malyshev
Semi-automatic annotation of Greek majuscule manuscripts: Steps towards integrated transcription and annotation.
FedCSIS 2024 - 19th Conference on Computer Science and Intelligence Systems. Belgrade, Serbia, Sep 08-11, 2024. DOI
Semi-automatic annotation of Greek majuscule manuscripts: Steps towards integrated transcription and annotation.
FedCSIS 2024 - 19th Conference on Computer Science and Intelligence Systems. Belgrade, Serbia, Sep 08-11, 2024. DOI
[19]
M. Fornasier • T. Klock • K. Riedl
Consensus-Based Optimization Methods Converge Globally.
SIAM Journal on Optimization 34.3. Jul. 2024. DOI
Consensus-Based Optimization Methods Converge Globally.
SIAM Journal on Optimization 34.3. Jul. 2024. DOI
[18]
C. Cipriani • A. Scagliotti • T. Wöhrer
A Minimax Optimal Control Approach for Robust Neural ODEs.
ECC 2024 - European Control Conference. Stockholm, Sweden, Jun 25-28, 2024. DOI
A Minimax Optimal Control Approach for Robust Neural ODEs.
ECC 2024 - European Control Conference. Stockholm, Sweden, Jun 25-28, 2024. DOI
[17]
A. Scagliotti • P. Colli Franzone
A subgradient method with constant step-size for l1-composite optimization.
Bollettino dell’Unione Matematica Italiana 17. Jun. 2024. DOI
A subgradient method with constant step-size for l1-composite optimization.
Bollettino dell’Unione Matematica Italiana 17. Jun. 2024. DOI
[16]
M. Brunner • M. Innerberger • A. Miraçi • D. Praetorius • J. Streitberger • P. Heid
Adaptive FEM with quasi-optimal overall cost for nonsymmetric linear elliptic PDEs.
IMA Journal of Numerical Analysis 44.3. May. 2024. DOI
Adaptive FEM with quasi-optimal overall cost for nonsymmetric linear elliptic PDEs.
IMA Journal of Numerical Analysis 44.3. May. 2024. DOI
[15]
R. Bailo • A. Barbaro • S. N. Gomes • K. Riedl • T. Roith • C. Totzeck • U. Vaes
CBX: Python and Julia packages for consensus-based interacting particle methods.
Preprint (Mar. 2024). arXiv
CBX: Python and Julia packages for consensus-based interacting particle methods.
Preprint (Mar. 2024). arXiv
[14]
C. Geldhauser • H. Diebel-Fischer
Is diverse and inclusive AI trapped in the gap between reality and algorithmizability?
NLDL 2024 - Northern Lights Deep Learning Conference. Tromsø, Norway, Jan 09-11, 2024. URL
Is diverse and inclusive AI trapped in the gap between reality and algorithmizability?
NLDL 2024 - Northern Lights Deep Learning Conference. Tromsø, Norway, Jan 09-11, 2024. URL
2023
[13]
F. Filbir • M. Tasche • A. Veselovska
Regularized Shannon sampling formulas related to the special affine Fourier transform.
Preprint (Nov. 2023). arXiv
Regularized Shannon sampling formulas related to the special affine Fourier transform.
Preprint (Nov. 2023). arXiv
[12]
K. Riedl
Leveraging Memory Effects and Gradient Information in Consensus-Based Optimisation: On Global Convergence in Mean-Field Law.
European Journal of Applied Mathematics. Oct. 2023. DOI
Leveraging Memory Effects and Gradient Information in Consensus-Based Optimisation: On Global Convergence in Mean-Field Law.
European Journal of Applied Mathematics. Oct. 2023. DOI
[11]
F. Hoppe • C. M. Verdun • H. Laus • F. Krahmer • H. Rauhut
Uncertainty Quantification For Learned ISTA.
MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI
Uncertainty Quantification For Learned ISTA.
MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI
[10]
P. Heid
A damped Kačanov scheme for the numerical solution of a relaxed p(x)-Poisson equation.
Partial Differential Equations and Applications 4.40. Aug. 2023. DOI
A damped Kačanov scheme for the numerical solution of a relaxed p(x)-Poisson equation.
Partial Differential Equations and Applications 4.40. Aug. 2023. DOI
[9]
F. Krahmer • H. Lyu • R. Saab • A. Veselovska • R. Wang
Quantization of Bandlimited Graph Signals.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI
Quantization of Bandlimited Graph Signals.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI
[8]
F. Krahmer • A. Veselovska
Digital Halftoning via Mixed-Order Weighted Σ∆ Modulation.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI
Digital Halftoning via Mixed-Order Weighted Σ∆ Modulation.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI
[7]
F. Krahmer • A. Veselovska
Enhanced Digital Halftoning via Weighted Sigma-Delta Modulation.
SIAM Journal on Imaging Sciences 16.3. Jul. 2023. DOI
Enhanced Digital Halftoning via Weighted Sigma-Delta Modulation.
SIAM Journal on Imaging Sciences 16.3. Jul. 2023. DOI
[6]
K. Riedl • T. Klock • C. Geldhauser • M. Fornasier
Gradient is All You Need?
Preprint (Jun. 2023). arXiv
Gradient is All You Need?
Preprint (Jun. 2023). arXiv
[5]
H. Huang • J. Qiu • K. Riedl
On the global convergence of particle swarm optimization methods.
Applied Mathematics and Optimization 88.2. May. 2023. DOI
On the global convergence of particle swarm optimization methods.
Applied Mathematics and Optimization 88.2. May. 2023. DOI
[4]
P. Heid
A short note on an adaptive damped Newton method for strongly monotone and Lipschitz continuous operator equations.
Archiv der Mathematik. Mar. 2023. URL
A short note on an adaptive damped Newton method for strongly monotone and Lipschitz continuous operator equations.
Archiv der Mathematik. Mar. 2023. URL
[3]
A. Scagliotti
Optimal control of ensembles of dynamical systems.
ESAIM - Control, Optimisation and Calculus of Variations 29.22. Mar. 2023. DOI
Optimal control of ensembles of dynamical systems.
ESAIM - Control, Optimisation and Calculus of Variations 29.22. Mar. 2023. DOI
2022
[2]
H. Huang • J. Qiu • K. Riedl
Consensus-Based Optimization for Saddle Point Problems.
Preprint (Dec. 2022). arXiv
Consensus-Based Optimization for Saddle Point Problems.
Preprint (Dec. 2022). arXiv
[1]
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