Martin Hutzenthaler

25 papers Journal 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Full history recursive multilevel Picard approximations suffer from the curse of dimensionality for the Hamilton-Jacobi-Bellman equation of a stochastic control problem. CoRR Martin Hutzenthaler, Tuan Anh Nguyen
2023	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations. J. Num. Math. Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse, Tuan Anh Nguyen
2022	J	`jnl`	Deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear partial differential equations. CoRR Petru A. Cioica-Licht, Martin Hutzenthaler, P. Tobias Werner
2022	J	`jnl`	Multilevel Picard approximations for high-dimensional decoupled forward-backward stochastic differential equations. CoRR Martin Hutzenthaler, Tuan Anh Nguyen
2022	J	`jnl`	Multilevel Picard approximations of high-dimensional semilinear partial differential equations with locally monotone coefficient functions. CoRR Tuan Anh Nguyen, Martin Hutzenthaler
2022	J	`jnl`	Overcoming the Curse of Dimensionality in the Numerical Approximation of Parabolic Partial Differential Equations with Gradient-Dependent Nonlinearities. Found. Comput. Math. Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2022	J	`jnl`	Stopped Brownian-increment tamed Euler method. CoRR Martin Hutzenthaler, Kai Kisker
2022	J	`jnl`	Strong convergence rate of Euler-Maruyama approximations in temporal-spatial Hölder-norms. J. Comput. Appl. Math. Martin Hutzenthaler, Tuan Anh Nguyen
2021	J	`jnl`	Convergence proof for stochastic gradient descent in the training of deep neural networks with ReLU activation for constant target functions. CoRR Martin Hutzenthaler, Arnulf Jentzen, Katharina Pohl, Adrian Riekert, Luca Scarpa
2021	J	`jnl`	Full history recursive multilevel Picard approximations for ordinary differential equations with expectations. CoRR Christian Beck, Martin Hutzenthaler, Arnulf Jentzen, Emilia Magnani
2021	J	`jnl`	Multilevel Picard approximations for McKean-Vlasov stochastic differential equations. CoRR Martin Hutzenthaler, Thomas Kruse, Tuan Anh Nguyen
2021	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations. CoRR Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse, Tuan Anh Nguyen
2021	J	`jnl`	Strong L CoRR Martin Hutzenthaler, Arnulf Jentzen, Benno Kuckuck, Joshua Lee Padgett
2021	J	`jnl`	Strong convergence rate of Euler-Maruyama approximations in temporal-spatial Hölder-norms. CoRR Tuan Anh Nguyen, Martin Hutzenthaler
2020	J	`jnl`	An overview on deep learning-based approximation methods for partial differential equations. CoRR Christian Beck, Martin Hutzenthaler, Arnulf Jentzen, Benno Kuckuck
2020	J	`jnl`	Multilevel Picard Approximations of High-Dimensional Semilinear Parabolic Differential Equations with Gradient-Dependent Nonlinearities. SIAM J. Numer. Anal. Martin Hutzenthaler, Thomas Kruse
2020	J	`jnl`	Multilevel Picard approximations for high-dimensional semilinear second-order PDEs with Lipschitz nonlinearities. CoRR Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse, Tuan Anh Nguyen
2020	J	`jnl`	Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations. CoRR Sebastian Becker, Ramon Braunwarth, Martin Hutzenthaler, Arnulf Jentzen, Philippe von Wurstemberger
2020	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of Allen-Cahn partial differential equations via truncated full-history recursive multilevel Picard approximations. J. Num. Math. Christian Beck, Fabian Hornung, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2019	J	`jnl`	On Multilevel Picard Numerical Approximations for High-Dimensional Nonlinear Parabolic Partial Differential Equations and High-Dimensional Nonlinear Backward Stochastic Differential Equations. J. Sci. Comput. Weinan E, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2019	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of Allen-Cahn partial differential equations via truncated full-history recursive multilevel Picard approximations. CoRR Christian Beck, Fabian Hornung, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2019	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of parabolic partial differential equations with gradient-dependent nonlinearities. CoRR Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2019	J	`jnl`	Strong convergence rates on the whole probability space for space-time discrete numerical approximation schemes for stochastic Burgers equations. CoRR Martin Hutzenthaler, Arnulf Jentzen, Felix Lindner, Primoz Pusnik
2018	J	`jnl`	Exponential integrability properties of numerical approximation processes for nonlinear stochastic differential equations. Math. Comput. Martin Hutzenthaler, Arnulf Jentzen, Xiaojie Wang
2011	J	`jnl`	Convergence of the Stochastic Euler Scheme for Locally Lipschitz Coefficients. Found. Comput. Math. Martin Hutzenthaler, Arnulf Jentzen