Fachbereich Mathematik und Informatik Angewandte Mathematik Münster

Topics in Mathematics Münster	T10: Deep learning and surrogate methods
Current Publications	• Beck C, Hutzenthaler M, Jentzen A, Kuckuck B An overview on deep learning-based approximation methods for partial differential equations. Discrete and Continuous Dynamical Systems - Series B Vol. 28 (6), 2023 online • Boussange, V.; Becker, S.; Jentzen, A.; Kuckuck, B.; Pellissier, L. Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions. , 2022 online • Jentzen A, Kuckuck B, Müller-Gronbach T, Yaroslavtseva L Counterexamples to local Lipschitz and local Hölder continuity with respect to the initial values for additive noise driven SDEs with smooth drift coefficient functions with at most polynomially growing derivatives. Discrete and Continuous Dynamical Systems - Series B Vol. 27 (7), 2022 online • Beck C, Jentzen A, Kuckuck B Full error analysis for the training of deep neural networks. Infinite Dimensional Analysis, Quantum Probability and Related Topics Vol. 25 (2), 2022 online • Jentzen A, Kuckuck B, Neufeld A, von Wurstemberger P Strong error analysis for stochastic gradient descent optimization algorithms. IMA Journal of Numerical Analysis Vol. 41 (1), 2021, pp 455-492 online • Hutzenthaler M, Jentzen A, Kuckuck B, Padgett JL Strong $L^p$-error analysis of nonlinear Monte Carlo approximations for high-dimensional semilinear partial differential equations. arXiv Vol. 0, 2021 online • Beneventano P, Cheridito P, Graeber R, Jentzen A, Kuckuck B Deep neural network approximation theory for high-dimensional functions. arXiv Vol. 0, 2021 online • Jentzen A, Kuckuck B, Müller-Gronbach T, Yaroslavtseva L On the strong regularity of degenerate additive noise driven stochastic differential equations with respect to their initial values. Journal of Mathematical Analysis and Applications Vol. 502 (2), 2021, pp Paper No. 125240 online • Kuckuck B, Rothe J Monotonicity, Duplication Monotonicity, and Pareto Optimality in the Scoring-Based Allocation of Indivisible Goods. , 2019, pp 173-189 online
E-Mail	bkuckuck@uni-muenster.de
Phone	+49 251 83-35128
FAX	+49 251 83-32729
Room	120.003
Secretary	Sekretariat Claudia Giesbert Frau Claudia Giesbert Telefon +49 251 83-33792 Fax +49 251 83-32729 Zimmer 120.002
Address	Dr. Benno Kuckuck Angewandte Mathematik Münster: Institut für Analysis und Numerik Fachbereich Mathematik und Informatik der Universität Münster Orléans-Ring 10 48149 Münster
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