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True Volterra equations are inherently non stationary and therefore do not admit $\textit{genuine stationary regimes}$ over finite horizons. This motivates the study of the finite-time behavior of the solutions to scaled inhomogeneous…

Probability · Mathematics 2025-12-11 Emmanuel Gnabeyeu , Gilles Pagès , Mathieu Rosenbaum

The aim of this work is to present, in self-contained form, results concerning fundamental and the most important questions related to linear stochastic Volterra equations of convolution type. The paper is devoted to study the existence and…

Probability · Mathematics 2007-12-31 Anna Karczewska

We give meaning to linear and semi-linear (possibly degenerate) parabolic partial differential equations with (affine) linear rough path noise and establish stability in a rough path metric. In the case of enhanced Brownian motion (Brownian…

Probability · Mathematics 2013-01-17 Peter Friz , Harald Oberhauser

In industrial applications it is quite common to use stochastic volatility models driven by semi-martingale Markov volatility processes. However, in order to fit exactly market volatilities, these models are usually extended by adding a…

Pricing of Securities · Quantitative Finance 2022-06-22 Enrico Dall'Acqua , Riccardo Longoni , Andrea Pallavicini

In this paper we investigate two numerical schemes for the simulation of stochastic Volterra equations driven by space--time L\'evy noise of pure-jump type. The first one is based on truncating the small jumps of the noise, while the second…

Probability · Mathematics 2016-01-19 Bohan Chen , Carsten Chong , Claudia Klüppelberg

Lyons' Rough Path theory is currently formulated in p-variation topology. We extend his main-result, the Universal Limit Theorem, to a stronger Hoelder topology. Several approximations to Brownian Rough Paths are studied. As application of…

Probability · Mathematics 2007-05-23 Peter K. Friz

Higher-order learning is fundamentally rooted in exploiting compositional features. It clearly hinges on enriching the representation by more elaborate interactions of the data which, in turn, tends to increase the model complexity of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Haoyu Yun , Hamid Krim , Yufang Bao

We associate backward and forward Kolmogorov equations to a class of fully nonlinear Stochastic Volterra Equations (SVEs) with convolution kernels $K$ that are singular at the origin. Working on a carefully chosen Hilbert space…

Probability · Mathematics 2025-09-29 Ioannis Gasteratos , Alexandre Pannier

We provide an account for the existence and uniqueness of solutions to rough differential equations under the framework of controlled rough paths. The case when the driving path is $\beta$-H\"older continuous, for $\beta>1/3$, is widely…

Classical Analysis and ODEs · Mathematics 2020-09-29 Horatio Boedihardjo , Xi Geng

We show how to use geometric arguments to prove that the terminal solution to a rough differential equation driven by a geometric rough path can be obtained by driving the same equation by a piecewise linear path. For this purpose, we…

Classical Analysis and ODEs · Mathematics 2022-02-01 Youness Boutaib

The systems of nonlinear Volterra integral equations of the first kind with jump discontinuous kernels are studied. The iterative numerical method for such nonlinear systems is proposed. Proposed method employs the modified…

Numerical Analysis · Mathematics 2019-10-22 A. N. Tynda , D. N. Sidorov , N. A. Sidorov

We obtain general weak existence and stability results for stochastic convolution equations with jumps under mild regularity assumptions, allowing for non-Lipschitz coefficients and singular kernels. Our approach relies on weak convergence…

Probability · Mathematics 2021-12-22 Eduardo Abi Jaber , Christa Cuchiero , Martin Larsson , Sergio Pulido

A theory of differential equations driven by a non-differentiable path has recently been developed by Lyons. We develop an alternative approach to this theory, using (modified Euler approximations), and investigate its applicability to…

Probability · Mathematics 2007-10-04 A. M. Davie

We discuss the application of multistep collocation methods to Volterra integral equations which contain a weakly singular kernel $(t-\tau)^{\alpha-1}$ with $0 <\alpha <1.$ Convergence orders of the methods are determined and their…

Numerical Analysis · Mathematics 2014-12-17 D. Nazari Susahab , S. Shahmorad

We make an attempt to understanding convolutional neural network by exploring the relationship between (deep) convolutional neural networks and Volterra convolutions. We propose a novel approach to explain and study the overall…

Machine Learning · Computer Science 2025-11-12 Tenghui Li , Guoxu Zhou , Yuning Qiu , Qibin Zhao

Rough sheets are two-parameter analogs of rough paths. In this work the theory of integration over functions of two parameters is extended to cover the case of irregular functions by developing an appropriate notion of rough sheet. The main…

Probability · Mathematics 2014-07-01 K. Chouk , M. Gubinelli

In this paper, stochastic Volterra equations driven by cylindrical Wiener process in Hilbert space are investigated. Sufficient conditions for existence of strong solutions are given. The key role is played by convergence of $\alpha$-times…

Probability · Mathematics 2007-06-14 Anna Karczewska , Carlos Lizama

We study the existence and uniqueness of solutions to stochastic differential equations with Volterra processes driven by L\'evy noise. For this purpose, we study in detail smoothness properties of these processes. Special attention is…

Probability · Mathematics 2020-08-26 Giulia Di Nunno , Yuliya Mishura , Kostiantyn Ralchenko

We prove a weak error estimate for the approximation in space and time of a semilinear stochastic Volterra integro-differential equation driven by additive space-time Gaussian noise. We treat this equation in an abstract framework, in which…

Numerical Analysis · Mathematics 2016-03-15 Adam Andersson , Mihály Kovács , Stig Larsson

In this article, we construct unique strong solutions to a class of stochastic Volterra differential equations driven by a singular drift vector field and a Wiener noise. Further, we examine the Sobolev differentiability of the strong…

Probability · Mathematics 2026-05-12 Emmanuel Coffie , Olivier Menoukeu-Pamen , Frank Proske