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20022026
most citedA regression-based Monte Carlo method to solve backward stochastic differential equations

425 citations

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60 papers · 1 filter

math.AP2025

Quantitative rigidity of the Wasserstein contraction under convolution

Max Fathi, Michael Goldman, Daniel Tsodyks

The aim of this paper is to investigate the contraction properties of -Wasserstein distances with respect to convolution in Euclidean spaces both qualitatively and quantitativel…

cond-mat.stat-mech20251 cited

Efficient Monte Carlo sampling of metastable systems using non-local collective variable updates

Christoph Schönle, Davide Carbone, Marylou Gabrié +2

Monte Carlo simulations are widely used to simulate complex molecular systems, but standard approaches suffer from metastability. Lately, the use of non-local proposal updates in a…

physics.optics2025

Spatio-temporal equilibrium thermodynamics of guided optical waves at positive and negative temperatures

Lucas Zanaglia, Josselin Garnier, Claire Michel +5

Optical thermalization has been recently studied in the 2D spatial evolution of (quasi-)monochromatic light waves propagating in multimode waveguides. Here, we investigate the spat…

q-fin.PM2025

Signature approach for pricing and hedging path-dependent options with frictions

Eduardo Abi Jaber, Donatien Hainaut, Edouard Motte

We introduce a novel signature approach for pricing and hedging path-dependent options with instantaneous and permanent market impact under a mean-quadratic variation criterion. Le…

math.PR2025

Efficient Simulation of Hawkes Processes using their Affine Volterra Structure

Eduardo Abi Jaber, Elie Attal, Dimitri Sotnikov

We introduce a novel and efficient simulation scheme for Hawkes processes on a fixed time grid, leveraging their affine Volterra structure. The key idea is to first simulate the in…

math.AP2025

Stability of non-conservative cross diffusion model and approximation by stochastic particle systems

Vincent Bansaye, Alexandre Bertolino, Ayman Moussa

We study the stability of non-conservative deterministic cross diffusion models and prove that they are approximated by stochastic population models when the populations become loc…