2 citations · 2 across the 1 of their papers we have counts for
5 papers
MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics
Luca De Gennaro Aquino, Stephan Eckstein
We study MinMax solution methods for a general class of optimization problems related to (and including) optimal transport. Theoretically, the focus is on fitting a large class of…
Lipschitz neural networks are dense in the set of all Lipschitz functions
Stephan Eckstein
This note shows that, for a fixed Lipschitz constant , one layer neural networks that are -Lipschitz are dense in the set of all -Lipschitz functions with respect to t…
Robust pricing and hedging of options on multiple assets and its numerics
Stephan Eckstein, Gaoyue Guo, Tongseok Lim +1
We consider robust pricing and hedging for options written on multiple assets given market option prices for the individual assets. The resulting problem is called the multi-margin…
Robust risk aggregation with neural networks
Stephan Eckstein, Michael Kupper, Mathias Pohl
We consider settings in which the distribution of a multivariate random variable is partly ambiguous. We assume the ambiguity lies on the level of the dependence structure, and tha…
Computation of optimal transport and related hedging problems via penalization and neural networks
Stephan Eckstein, Michael Kupper
This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize th…