Hutzenthaler, Martin

1. Convergence proof for stochastic gradient descent in the training of deep neural networks with ReLU activation for constant target functions
   2021/12/13 by Hutzenthaler, Martin, Jentzen, Arnulf, Pohl, Katharina +2 · 2 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Probability (math.PR)
2. On the speed of convergence of Picard iterations of backward stochastic differential equations
   2021/07/05 by Hutzenthaler, Martin, Kruse, Thomas, Nguyen, Tuan Anh · 1 citation
   #60G99 #60H99 #65C99 #FOS: Mathematics #Probability (math.PR)
3. Deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear partial differential equations
   2022/05/28 by Petru A. Cioica-Licht, Martin Hutzenthaler, Cioica-Licht, Petru A. +3 · 1 citation
   Physics and Astronomy · Engineering · Mathematics · #Model Reduction and Neural Networks #Advanced Numerical Methods in Computational Mathematics #Numerical methods in inverse problems
4. Strong L^p-error analysis of nonlinear Monte Carlo approximations for high-dimensional semilinear partial differential equations
   2021/10/15 by Hutzenthaler, Martin, Jentzen, Arnulf, Kuckuck, Benno +1 · 1 citation
   #FOS: Mathematics #Numerical Analysis (math.NA) #Probability (math.PR)