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20162025
most citedA proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations

84 citations · 138 across the 17 of their papers we have counts for

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5 papers · 1 filter

math.PR2022

A path-dependent stochastic Gronwall inequality and strong convergence rate for stochastic functional differential equations

Martin Hutzenthaler, Tuan Anh Nguyen

We derive a stochastic Gronwall lemma with suprema over the paths in the upper bound of the assumed affine-linear growth assumption. This allows applications to Itô processes with…

math.PR2022★ 2 cited

Multilevel Picard approximations for high-dimensional decoupled forward-backward stochastic differential equations

Martin Hutzenthaler, Tuan Anh Nguyen

Backward stochastic differential equations (BSDEs) appear in numeruous applications. Classical approximation methods suffer from the curse of dimensionality and deep learning-based…

math.PR2021

On the speed of convergence of Picard iterations of backward stochastic differential equations

Martin Hutzenthaler, Thomas Kruse, Tuan Anh Nguyen

It is a well-established fact in the scientific literature that Picard iterations of backward stochastic differential equations with globally Lipschitz continuous nonlinearity conv…

math.PR2021★ 15 cited

Multilevel Picard approximations for McKean-Vlasov stochastic differential equations

Martin Hutzenthaler, Thomas Kruse, Tuan Anh Nguyen

In the literatur there exist approximation methods for McKean-Vlasov stochastic differential equations which have a computational effort of order . In this article we introduce…

math.PR2016★ 24 cited

Quenched invariance principles for the random conductance model on a random graph with degenerate ergodic weights

Jean-Dominique Deuschel, Tuan Anh Nguyen, Martin Slowik

We consider a stationary and ergodic random field that is parameterized by the edge set of the Euclidean lattice , . The random varia…