Stochastic Analysis and Applications 2025

Edited by Dan Crisan (), Ilya Chevyrev (), Thomas Cass (), James Foster (), Christian Litterer () and Cristopher Salvi ()

in Springer Books from Springer

Date: 2026
ISBN: 978-3-032-03914-9
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Chapters in this book:

Approximating the Signature of Brownian Motion for High Order SDE Simulation

James Foster

Randomisation of Rough Stochastic Differential Equations

Peter K. Friz, Khoa Lê and Huilin Zhang

A Canonical Signature-Based Feature Set for Multivariate Time Series Classification

James Morrill, Adeline Fermanian, Patrick Kidger and Terry Lyons

Twin Brownian Particle Method for the Study of Oberbeck-Boussinesq Fluid Flows

Jiawei Li, Zhongmin Qian and Mingyu Xu

Lower Bounds for the Support of Cubature Measures on Wiener Space and Optimal Degree-Five Constructions

Christian Litterer

Free Groups and Signatures

Yves Le Jan

A Representation for the Expected Signature of Brownian Motion up to the First Exit Time of the Planar Unit Disc

Horatio Boedihardjo, Lin Hao He and Lisa Wang

Asymptotic Expansions of Central Limit Distances in Vaserstein Metrics

A. M. Davie

A Neural RDE-Based Model for Solving Path-Dependent Parabolic PDEs

Bowen Fang, Hao Ni and Yue Wu

A Data-Driven Market Simulator for Small Data Environments

Hans Bühler, Blanka Horvath, Terry Lyons, Imanol Perez Arribas and Ben Wood

Mimicking and Conditional Control with Hard Killing

Rene Carmona and Daniel Lacker

Continuous Random Field Solutions to Parabolic SPDEs on P.C.F. Fractals

Ben Hambly and Weiye Yang

Pricing American Options Under Rough Volatility Using Signatures

Christian Bayer, Luca Pelizzari and Jia-Jie Zhu

A New Architecture of High-Order Deep Neural Networks that Learn Martingales

Yuming Ma and Syoiti Ninomiya

Permutation Recovery of Spikes in Noisy High-Dimensional Tensor Estimation

Gérard Ben Arous, Cédric Gerbelot and Vanessa Piccolo

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

Csaba Tóth, Danilo Jr Dela Cruz and Harald Oberhauser

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DOI: 10.1007/978-3-032-03914-9

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