Mathias Oster

11 papers A* 1Journal 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Preconditioning and Numerical Stability in Neural Network Training for Parametric PDEs.
CoRR
Markus Bachmayr, Wolfgang Dahmen, Chenguang Duan, Mathias Oster
2025 J jnl
A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control.
Dyn. Games Appl.
Mathias Oster, Luca Saluzzi, Tizian Wenzel
2025 J jnl
Neural network approximation of regularized density functionals.
CoRR
Mihály András Csirik, Andre Laestadius, Mathias Oster
2025 J jnl
Optimization-Free Diffusion Model - A Perturbation Theory Approach.
CoRR
Yuehaw Khoo, Mathias Oster, Yifan Peng
2024 J jnl
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control.
CoRR
Mathias Oster, Luca Saluzzi, Tizian Wenzel
2024 J jnl
Coupled Cluster Theory: Toward an Algebraic Geometry Formulation.
SIAM J. Appl. Algebra Geom.
Fabian M. Faulstich, Mathias Oster
2024 A* conf
S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization.
NeurIPS
Licheng Zhu, Mathias Oster, Yuehaw Khoo
2024 J jnl
Variationally Correct Neural Residual Regression for Parametric PDEs: On the Viability of Controlled Accuracy.
CoRR
Markus Bachmayr, Wolfgang Dahmen, Mathias Oster
2022 J jnl
Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats.
SIAM J. Sci. Comput.
Mathias Oster, Leon Sallandt, Reinhold Schneider
2022 J jnl
Approximative Policy Iteration for Exit Time Feedback Control Problems Driven by Stochastic Differential Equations using Tensor Train Format.
Multiscale Model. Simul.
Konstantin Fackeldey, Mathias Oster, Leon Sallandt, Reinhold Schneider
2021 J jnl
Approximating optimal feedback controllers of finite horizon control problems using hierarchical tensor formats.
CoRR
Mathias Oster, Leon Sallandt, Reinhold Schneider