{"id":781,"date":"2025-08-27T13:16:28","date_gmt":"2025-08-27T11:16:28","guid":{"rendered":"https:\/\/uni-freiburg.de\/aam\/?page_id=781"},"modified":"2025-08-27T13:16:31","modified_gmt":"2025-08-27T11:16:31","slug":"pubs","status":"publish","type":"page","link":"https:\/\/uni-freiburg.de\/aam\/agsa\/pubs\/","title":{"rendered":"Publications"},"content":{"rendered":"\n
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Preprints<\/h2>\n\n\n
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3<\/td>\nAritz Bercher, Lukas Gonon, Arnulf Jentzen, and Diyora Salimova. Weak error analysis for stochastic gradient descent optimization algorithms. 2020.<\/td>\narXiv<\/a><\/td>\n<\/tr>\n
2<\/td>\nMatteo 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.<\/td>\narXiv<\/a><\/td>\n<\/tr>\n
1<\/td>\nArnulf Jentzen, Sara Mazzonetto, and Diyora Salimova. Existence and uniqueness properties for solutions of a class of Banach space valued evolution equations. 2018.<\/td>\narXiv<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n
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Articles<\/h2>\n\n\n
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11<\/td>\nJ. Settelmeier, S. Goetze, J. Boshart, J. Fu., S. N. Steiner, M. Gesell, P. J. Sch\u00fcffler, 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<\/em>, 24(6):2816-2831, 2025.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
10<\/td>\nFabian Hornung, Arnulf Jentzen, and Diyora Salimova. Space-time deep neural network approximations for high-dimensional partial differential equations. J. Comput. Math.<\/em>, 43(4):918–975, 2025.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
9<\/td>\nTill 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<\/em>, 58(15):1801-1811, 2024.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
8<\/td>\nJonas Baggenstos and Diyora Salimova. Approximation properties of residual neural networks for Kolmogorov PDEs. Discrete Contin. Dyn. Syst. Ser. B<\/em>, 28(5):3193–3215, 2023.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
7<\/td>\nPhilipp Grohs, Arnulf Jentzen, and Diyora Salimova. Deep neural network approximations for solutions of PDEs based on Monte Carlo algorithms. Partial Differ. Equ. Appl.<\/em>, 3(4):Paper No. 45, 41, 2022.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
6<\/td>\nArnulf 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.<\/em>, 19(5):1167–1205, 2021.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
5<\/td>\nSara Mazzonetto and Diyora Salimova. Existence, uniqueness, and numerical approximations for stochastic Burgers equations. Stoch. Anal. Appl.<\/em>, 38(4):623–646, 2020.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
4<\/td>\nArnulf Jentzen, Diyora Salimova, and Timo Welti. Strong convergence for explicit space-time discrete numerical approximation methods for stochastic Burgers equations. J. Math. Anal. Appl.<\/em>, 469(2):661–704, 2019.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
3<\/td>\nMartin 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.<\/em>, 716(6):1489–1529, 2018.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
2<\/td>\nM\u00e1t\u00e9 Gerencs\u00e9r, Arnulf Jentzen, and Diyora Salimova. On stochastic differential equations with arbitrarily slow convergence rates for strong approximation in two space dimensions. Proc. A.<\/em>, 473(2207):20170104, 16, 2017.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n
1<\/td>\nZarif O. Ibragimov and Diyora F. Salimova. On an inequality in lp<\/sub>(C) involving Basel problem. Elem. Math.<\/em>, 70(2):79–81, 2015.<\/td>\nDOI<\/a>\u00a0| http<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n
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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.<\/p>\n","protected":false},"author":681,"featured_media":0,"parent":310,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_trash_the_other_posts":false,"editor_notices":[],"footnotes":""},"class_list":["post-781","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/pages\/781","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/users\/681"}],"replies":[{"embeddable":true,"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/comments?post=781"}],"version-history":[{"count":9,"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/pages\/781\/revisions"}],"predecessor-version":[{"id":791,"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/pages\/781\/revisions\/791"}],"up":[{"embeddable":true,"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/pages\/310"}],"wp:attachment":[{"href":"https:\/\/uni-freiburg.de\/aam\/wp-json\/wp\/v2\/media?parent=781"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}