Publications

Preprints

3	Aritz Bercher, Lukas Gonon, Arnulf Jentzen, and Diyora Salimova. Weak error analysis for stochastic gradient descent optimization algorithms. 2020.	arXiv
2	Matteo Beccari, Martin Hutzenthaler, Arnulf Jentzen, Ryan Kurniawan, Felix Lindner, and Diyora Salimova. Strong and weak divergence of exponential and linear-implicit Euler approximations for stochastic partial differential equations with superlinearly growing nonlinearities. 2019.	arXiv
1	Arnulf Jentzen, Sara Mazzonetto, and Diyora Salimova. Existence and uniqueness properties for solutions of a class of Banach space valued evolution equations. 2018.	arXiv

Articles

11	J. Settelmeier, S. Goetze, J. Boshart, J. Fu., S. N. Steiner, M. Gesell, P. J. Schüffler, D. Salimova, P. G. A. Pedrioli, and B. Wollscheid. MultiOmicsAgent: Guided extreme gradient-boosted decision trees-based approaches for biomarker-candidate discovery in multi-omics data. Journal of Proteome Research, 24(6):2816-2831, 2025.	DOI \| http
10	Fabian Hornung, Arnulf Jentzen, and Diyora Salimova. Space-time deep neural network approximations for high-dimensional partial differential equations. J. Comput. Math., 43(4):918–975, 2025.	DOI \| http
9	Till Herrmann, Dariusz Niedziela, Diyora Salimova, and Timo Schweiger. IPredicting the fiber orientation of injection molded components and the geometry influence with neural networks. Journal of Composite Materials, 58(15):1801-1811, 2024.	DOI \| http
8	Jonas Baggenstos and Diyora Salimova. Approximation properties of residual neural networks for Kolmogorov PDEs. Discrete Contin. Dyn. Syst. Ser. B, 28(5):3193–3215, 2023.	DOI \| http
7	Philipp Grohs, Arnulf Jentzen, and Diyora Salimova. Deep neural network approximations for solutions of PDEs based on Monte Carlo algorithms. Partial Differ. Equ. Appl., 3(4):Paper No. 45, 41, 2022.	DOI \| http
6	Arnulf Jentzen, Diyora Salimova, and Timo Welti. A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients. Commun. Math. Sci., 19(5):1167–1205, 2021.	DOI \| http
5	Sara Mazzonetto and Diyora Salimova. Existence, uniqueness, and numerical approximations for stochastic Burgers equations. Stoch. Anal. Appl., 38(4):623–646, 2020.	DOI \| http
4	Arnulf Jentzen, Diyora Salimova, and Timo Welti. Strong convergence for explicit space-time discrete numerical approximation methods for stochastic Burgers equations. J. Math. Anal. Appl., 469(2):661–704, 2019.	DOI \| http
3	Martin Hutzenthaler, Arnulf Jentzen, and Diyora Salimova. Strong convergence of full-discrete nonlinearity-truncated accelerated exponential Euler-type approximations for stochastic Kuramoto-Sivashinsky equations. Commun. Math. Sci., 716(6):1489–1529, 2018.	DOI \| http
2	Máté Gerencsér, Arnulf Jentzen, and Diyora Salimova. On stochastic differential equations with arbitrarily slow convergence rates for strong approximation in two space dimensions. Proc. A., 473(2207):20170104, 16, 2017.	DOI \| http
1	Zarif O. Ibragimov and Diyora F. Salimova. On an inequality in l_p(C) involving Basel problem. Elem. Math., 70(2):79–81, 2015.	DOI \| http