Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model. - Patrick Gelß; Sebastian Matera; Christof Schütte (J. Comput. Phys., 2016)

Nearest-neighbor interaction systems in the tensor-train format. - Patrick Gelß; Stefan Klus; Sebastian Matera; Christof Schütte (J. Comput. Phys., 2017)

Tensor-Based Algorithms for Image Classification. - Stefan Klus; Patrick Gelß (Algorithms, 2019)

Tensor-based EDMD for the Koopman analysis of high-dimensional systems. - Feliks Nüske; Patrick Gelß; Stefan Klus; Cecilia Clementi (CoRR, 2019)

Feature space approximation for kernel-based supervised learning. - Patrick Gelß; Stefan Klus; Ingmar Schuster; Christof Schütte (Knowl. Based Syst., 2021)

Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. - Stefan Klus; Patrick Gelß; Feliks Nüske; Frank Noé (Mach. Learn. Sci. Technol., 2021)

Continuous optimization methods for the graph isomorphism problem. - Stefan Klus; Patrick Gelß (CoRR, 2023)

Fredholm Integral Equations for Function Approximation and the Training of Neural Networks. - Patrick Gelß; Aizhan Issagali; Ralf Kornhuber (SIAM J. Math. Data Sci., 2024)

Workflow-Driven Modeling for the Compute Continuum: An Optimization Approach to Automated System and Workload Scheduling. - Aasish Kumar Sharma; Christian Boehme; Patrick Gelß; Ramin Yahyapour; Julian M. Kunkel (COMPSAC, 2025)