Approximative Policy Iteration for Exit Time Feedback Control Problems Driven by Stochastic Differential Equations using Tensor Train Format. - Konstantin Fackeldey; Mathias Oster; Leon Sallandt; Reinhold Schneider (Multiscale Model. Simul., 2022)

Approximating Optimal feedback Controllers of Finite Horizon Control Problems Using Hierarchical Tensor Formats. - Mathias Oster; Leon Sallandt; Reinhold Schneider (SIAM J. Sci. Comput., 2022)

S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization. - Licheng Zhu; Mathias Oster; Yuehaw Khoo (NeurIPS, 2024)

Variationally Correct Neural Residual Regression for Parametric PDEs: On the Viability of Controlled Accuracy. - Markus Bachmayr; Wolfgang Dahmen; Mathias Oster (CoRR, 2024)

Coupled Cluster Theory: Toward an Algebraic Geometry Formulation. - Fabian M. Faulstich; Mathias Oster (SIAM J. Appl. Algebra Geom., 2024)

Optimization-Free Diffusion Model - A Perturbation Theory Approach. - Yuehaw Khoo; Mathias Oster; Yifan Peng (CoRR, 2025)

A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control. - Mathias Oster; Luca Saluzzi; Tizian Wenzel (Dyn. Games Appl., 2025)