Baran, B.: Optimal Control of a Stefan Problem with Gradient-Based Methods in FEniCS. Master, Otto-von-Guericke Universität, Magdeburg (2016)

Behr, M.: Optimization and Stabilization of Incompressible Flows via Boundary Control in M.E.S.S. Master, Otto-von-Guericke Universität, Magdeburg (2015)

Hund, M.: Zeitbereichs-Modellreduktion und Sylvester-Gleichungen. Master, Otto-von-Guericke Universität, Magdeburg (2015)

Alam, G. M.: Fast Iterative Solution of Large Scale Statistical Inverse Problem. Master, Stockholm University, Stockholm, Sweden (2013)

Bosch, J.: Fast solvers for Cahn-Hilliard variational inequalities. Master, Otto-von-Guericke Universität, Magdeburg (2012)

Jendersie, R.: Model Order Reduction of Linear Discrete-Time Systems. Bachelor, Otto-von-Guericke Universität, Magdeburg (2019)

Pauer, G.: Numerisches Lösen großer dünnbesetzter Matrixgleichungen auf CUDA GPUs. Bachelor, Otto-von-Guericke Universität, Magdeburg (2015)

Werner, S. W. R.: Numerische Berechnung der Eigenwerte großer Hamiltonisch-positiver Matrizen. Bachelor, Otto-von-Guericke Universität, Magdeburg (2014)

Hermann, S.: Simultane iterative Lösung der adjungierten linearen Gleichungssysteme in der dualen Niedrig-Rang ADI Iteration für Lyapunovgleichungen. Bachelor, Otto-von-Guericke Universität, Magdeburg (2014)

Penke, C.: Implementierung der Newton-Iteration zur Berechnung des Signums eines Matrix-Büschels mit Hilfe der MAGMA-Softwarebibliothek. Bachelor, Otto-von-Guericke Universität, Magdeburg (2014)

Baran, B.: Numerisches Lösen großer dünnbesetzter Matrixgleichungen in Python. Bachelor, Otto-von-Guericke Universität, Magdeburg (2013)

Behr, M.: Second Order LQR-Problems in M.E.S.S. Bachelor, Otto-von-Guericke-Universität, Magdeburg (2013)

Hund, M.: Adaptive Berechnung der ADI Shiftparameter in der Niedrig-Rang-Galerkin-ADI. Bachelor, Otto-von-Guericke Universität, Magdeburg (2012)

Himpe, C.; Grundel, S.; Benner, P.: Model Order Reduction for Gas and Energy Networks. (2020)

Daas, H. A.; Ballard, G.; Benner, P.: Parallel Algorithms for Tensor Train Arithmetic. (2020)

Grundel, S.; Heyder, S.; Hotz, T.; Ritschel, T. K.S.; Sauerteig, P.; Worthmann, K.: How much testing and social distancing is required to control COVID-19? Some insight based on an age-differentiated compartmental model. (2020)

Beddig, R. S.; Benner, P.; Dorschky, I.; Reis, T.; Schwerdtner, P.; Voigt, M.; Werner, S. W. R.: Structure-Preserving Model Reduction for Dissipative Mechanical Systems. (2020)

Benner, P.; Goyal, P. K.; Heiland, J.; Pontes Duff, I.: Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows. (2020)

Sarna, N.; Giesselmann, J.; Benner, P.: Data-Driven Snapshot Calibration via Monotonic Feature Matching. (2020)

Benner, P.; Fassbender, H.; Saltenberger, P.: A Rational Even-IRA Algorithm for the Solution of T-even Polynomial Eigenvalue Problems. (2020)

Alla, A.; Gräßle, C.; Hinze, M.: Time Adaptivity in Model Predictive Control. (2020)

Benner, P.; Heiland, J.: Space and Chaos-Expansion Galerkin POD Low-order Discretization of PDEs for Uncertainty Quantification. (2020)

Weinhandl, R.; Benner, P.; Richter, T.: A Low-rank Method for Parameter-dependent Fluid-structure Interaction Discretizations with Hyperelasticity. (2020)

Benner, P.; Penke, C.: Efficient and Accurate Algorithms for Solving the Bethe-Salpeter Eigenvalue Problem for Crystalline Systems. (2020)

Yıldız, S.; Goyal, P. K.; Benner, P.; Karasözen, B.: Data-Driven Learning of Reduced-order Dynamics for a Parametrized Shallow Water Equation. (2020)

Heiland, J.; Zuazua, E.: Classical System Theory Revisited for Turnpike in Standard State Space Systems and Impulse Controllable Descriptor Systems. (2020)

Benner, P.; Gugercin, S.; Werner, S. W. R.: Structure-Preserving Interpolation for Model Reduction of Parametric Bilinear Systems. (2020)

Benner, P.; Stillfjord, T.; Trautwein, C.: A Linear Implicit Euler Method for the Finite Element Discretization of a Controlled Stochastic Heat Equation. (2020)

Grundel, S.; Herty, M.: Hyperbolic Discretization via Riemann Invariants. (2020)

Cherifi, K.; Goyal, P. K.; Benner, P.: A Non-Intrusive Method to Inferring Linear Port-Hamiltonian Realizations using Time-Domain Data. (2020)