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Disambiguation of "Jentzen, Arnulf"

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Gradient descent provably escapes saddle points in the training of shallow ReLU networks.

, , and . CoRR, (2022)

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Arnulf Jentzen

Richard Jentzen

Walter Jentzen

Volker Jentzen

Richard Jentzen

 

Other publications of authors with the same name

Deep neural network approximations for Monte Carlo algorithms, , and . (2019)cite arxiv:1908.10828Comment: 45 pages.Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions., , and . J. Mach. Learn. Res., (2020)Overcoming the curse of dimensionality in the numerical approximation of Allen-Cahn partial differential equations via truncated full-history recursive multilevel Picard approximations., , , , and . J. Num. Math., 28 (4): 197-222 (2020)Galerkin Approximations for the Stochastic Burgers Equation., and . SIAM J. Numerical Analysis, 51 (1): 694-715 (2013)Solving the Kolmogorov PDE by Means of Deep Learning., , , , and . J. Sci. Comput., 88 (3): 73 (2021)On Multilevel Picard Numerical Approximations for High-Dimensional Nonlinear Parabolic Partial Differential Equations and High-Dimensional Nonlinear Backward Stochastic Differential Equations., , , and . J. Sci. Comput., 79 (3): 1534-1571 (2019)Space-time error estimates for deep neural network approximations for differential equations., , , and . Adv. Comput. Math., 49 (1): 4 (February 2023)Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations., , and . CoRR, (2023)Full history recursive multilevel Picard approximations for ordinary differential equations with expectations., , , and . CoRR, (2021)Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory., , and . CoRR, (2023)