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1

Learning the random variables in Monte Carlo simulations wi..:

Becker, Sebastian ; Jentzen, Arnulf ; Müller, Marvin S.
info:eu-repo/semantics/altIdentifier/doi/10.1111/mafi.12405. , 2024

Link: https://hdl.handle.net/2..

2

On the Itô-Alekseev-Gröbner formula for stochastic differen..:

Hudde, Anselm ; Hutzenthaler, Martin ; Jentzen, Arnulf.
info:eu-repo/semantics/altIdentifier/arxiv/1812.09857. , 2023

Link: https://hal.science/hal-..

3

A Proof that Artificial Neural Networks Overcome the Curse ..:

Grohs, Philipp ; Hornung, Fabian ; Jentzen, Arnulf.
info:eu-repo/semantics/altIdentifier/wos/000991353000001. , 2023

Link: https://publikationen.bi..

4

An efficient Monte Carlo scheme for Zakai equations:

Beck, Christian ; Becker, Sebastian ; Cheridito, Patrick..
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cnsns.2023.107438. , 2023

Link: https://hdl.handle.net/2..

5

Algorithmically Designed Artificial Neural Networks (ADANNs..:

Jentzen, Arnulf ; Riekert, Adrian ; von Wurstemberger, Philippe
http://arxiv.org/abs/2302.03286. , 2023

Link: http://arxiv.org/abs/230..

6

Deep learning approximations for non-local nonlinear PDEs w..:

Boussange, Victor ; Becker, Sebastian ; Jentzen, Arnulf..
info:eu-repo/semantics/altIdentifier/doi/10.1007/s42985-023-00244-0. , 2023

Link: https://hdl.handle.net/2..

7

Mathematical Introduction to Deep Learning: Methods, Implem..:

Jentzen, Arnulf ; Kuckuck, Benno ; von Wurstemberger, Philippe
http://arxiv.org/abs/2310.20360. , 2023

Link: http://arxiv.org/abs/231..

8

Space-time error estimates for deep neural network approxim..:

Grohs, Philipp ; Hornung, Fabian ; Jentzen, Arnulf..
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10444-022-09970-2. , 2023

Link: https://hdl.handle.net/2..

9

On the Itô-Alekseev-Gröbner formula for stochastic differen..:

Hudde, Anselm ; Hutzenthaler, Martin ; Jentzen, Arnulf.
info:eu-repo/semantics/altIdentifier/arxiv/1812.09857. , 2023

Link: https://hal.science/hal-..

10

Existence, uniqueness, and convergence rates for gradient f..:

Eberle, S. (Simon) ; Jentzen, A. (Arnulf) ; Riekert, A. (Adrian).
info:eu-repo/semantics/reference/doi/10.3934/era.2023128. , 2023

Link: https://nbn-resolving.or..

11

On the existence of minimizers in shallow residual ReLU neu..:

Dereich, Steffen ; Jentzen, Arnulf ; Kassing, Sebastian
http://arxiv.org/abs/2302.14690. , 2023

Link: http://arxiv.org/abs/230..

12

Nonlinear Monte Carlo methods with polynomial runtime for B..:

Beck, Christian ; Jentzen, Arnulf ; Kleinberg, Konrad.
http://arxiv.org/abs/2303.03390. , 2023

Link: http://arxiv.org/abs/230..

13

Space-time error estimates for deep neural network approxim..:

Grohs, Philipp ; Hornung, Fabian ; Jentzen, Arnulf.
info:eu-repo/semantics/altIdentifier/wos/000912469100001. , 2023

Link: https://publikationen.bi..

14

The necessity of depth for artificial neural networks to ap..:

Gonon, Lukas ; Graeber, Robin ; Jentzen, Arnulf
http://arxiv.org/abs/2301.08284. , 2023

Link: http://arxiv.org/abs/230..

15

Deep neural networks with ReLU, leaky ReLU, and softplus ac..:

Ackermann, Julia ; Jentzen, Arnulf ; Kruse, Thomas..
http://arxiv.org/abs/2309.13722. , 2023

Link: http://arxiv.org/abs/230..

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