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. - Arnulf Jentzen; Diyora Salimova; Timo Welti (CoRR, 2018)

Deep neural network approximations for Monte Carlo algorithms. - Philipp Grohs; Arnulf Jentzen; Diyora Salimova (CoRR, 2019)

Space-time deep neural network approximations for high-dimensional partial differential equations. - Fabian Hornung; Arnulf Jentzen; Diyora Salimova (CoRR, 2020)

Weak error analysis for stochastic gradient descent optimization algorithms. - Aritz Bercher; Lukas Gonon; Arnulf Jentzen; Diyora Salimova (CoRR, 2020)

Approximation properties of Residual Neural Networks for Kolmogorov PDEs. - Jonas Baggenstos; Diyora Salimova (CoRR, 2021)