25 citations · 67 across the 18 of their papers we have counts for
29 papers
Forward Reverse Kernel Regression for the Schrödinger bridge problem
Denis Belomestny, John. Schoenmakers
In this paper, we study the Schrödinger Bridge Problem (SBP), which is central to entropic optimal transport. For general reference processes and begin--endpoint distributions, we…
Weighted mesh algorithms for general Markov decision processes: Convergence and tractability
Denis Belomestny, John Schoenmakers
We introduce a mesh-type approach for tackling discrete-time, finite-horizon Markov Decision Processes (MDPs) characterized by state and action spaces that are general, encompassin…
Primal and dual optimal stopping with signatures
Christian Bayer, Luca Pelizzari, John Schoenmakers
We propose two signature-based methods to solve the optimal stopping problem - that is, to price American options - in non-Markovian frameworks. Both methods rely on a global appro…
Primal-dual regression approach for Markov decision processes with general state and action space
Denis Belomestny, John Schoenmakers
We develop a regression based primal-dual martingale approach for solving finite time horizon MDPs with general state and action space. As a result, our method allows for the const…
A Reproducing Kernel Hilbert Space approach to singular local stochastic volatility McKean-Vlasov models
Christian Bayer, Denis Belomestny, Oleg Butkovsky +1
Motivated by the challenges related to the calibration of financial models, we consider the problem of numerically solving a singular McKean-Vlasov equation $$ d X_t= σ(t,X_t) X_t…
Optimal stopping with signatures
Christian Bayer, Paul Hager, Sebastian Riedel +1
We propose a new method for solving optimal stopping problems (such as American option pricing in finance) under minimal assumptions on the underlying stochastic process . We co…