C. Schwab

most citedHigher-order Quasi-Monte Carlo Training of Deep Neural Networks

3 citations · 5 across the 3 of their papers we have counts for

collaborators

3 papers

math.NA2020★ 3 cited

Higher-order Quasi-Monte Carlo Training of Deep Neural Networks

M. Longo, S. Mishra, T. K. Rusch +1

We present a novel algorithmic approach and an error analysis leveraging Quasi-Monte Carlo points for training deep neural network (DNN) surrogates of Data-to-Observable (DtO) maps…

math.NA2020★ 1 cited

Quantized tensor FEM for multiscale problems: diffusion problems in two and three dimensions

V. Kazeev, I. Oseledets, M. Rakhuba +1

Homogenization in terms of multiscale limits transforms a multiscale problem with $n + 1$ asymptotically separated microscales posed on a physical domain $D \subset R^{d}$ int…

math.NA2019★ 1 cited

Tensor Rank bounds for Point Singularities in $R^{3}$

Carlo Marcati, Maxim Rakhuba, Christoph Schwab

We analyze rates of approximation by quantized, tensor-structured representations of functions with isolated point singularities in $R^{3}$ . We consider functions in counta…

Higher-order Quasi-Monte Carlo Training of Deep Neural Networks

Quantized tensor FEM for multiscale problems: diffusion problems in two and three dimensions

Tensor Rank bounds for Point Singularities in R3

Tensor Rank bounds for Point Singularities in $R^{3}$