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Within this paper, we introduce partially and fully decoupled time stepping schemes for linear thermo-poroelasticity. This means that the mechanics, heat, and flow equations can be solved sequentially. We provide sufficient conditions on…

Numerical Analysis · Mathematics 2026-03-17 R. Altmann , R. Maier , J. Schmeck

We propose a new scheme for the long time approximation of a diffusion when the drift vector field is not globally Lipschitz. Under this assumption, regular explicit Euler scheme --with constant or decreasing step-- may explode and implicit…

Probability · Mathematics 2018-02-20 Vincent Lemaire

We study the traditional backward Euler method for $m$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H > 1/2$ whose drift coefficient satisfies the one-sided Lipschitz condition.…

Numerical Analysis · Mathematics 2022-05-30 Hao Zhou , Yaozhong Hu , Yanghui Liu

We provide faster algorithms for the problem of Gaussian summation, which occurs in many machine learning methods. We develop two new extensions - an O(Dp) Taylor expansion for the Gaussian kernel with rigorous error bounds and a new error…

Machine Learning · Computer Science 2012-07-02 Dongryeol Lee , Alexander G. Gray

We consider controlled differential equations and give new estimates for higher order Euler schemes. Our proofs are inspired by recent work of A. M. Davie who considers first and second order schemes. In order to implement the general case…

Classical Analysis and ODEs · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

In this paper, we introduce an algorithm that provides approximate solutions to semi-linear ordinary differential equations with highly oscillatory solutions, which, after an appropriate change of variables, can be rewritten as…

Numerical Analysis · Mathematics 2025-02-13 M. P. Calvo , J. Makazaga , A. Murua

Rough paths techniques give the ability to define solutions of stochastic differential equations driven by signals $X$ which are not semimartingales and whose $p$-variation is finite only for large values of $p$. In this context, rough…

Probability · Mathematics 2020-05-15 Yanghui Liu , Zachary Selk , Samy Tindel

In this work, we study and extend a class of semi-Lagrangian exponential methods, which combine exponential time integration techniques, suitable for integrating stiff linear terms, with a semi-Lagrangian treatment of nonlinear advection…

Numerical Analysis · Mathematics 2025-04-25 João Guilherme Caldas Steinstraesser , Martin Schreiber , Pedro da Silva Peixoto

In this brief, we discuss the implementation of a third order semi-implicit differentiator as a complement of the recent work by the author that proposes an interconnected semi-implicit Euler double differentiators algorithm through Taylor…

Numerical Analysis · Mathematics 2024-08-02 Loïc Michel , Jean-Pierre Barbot

In this paper we consider a sub-diffusion problem where the fractional time derivative is approximated either by the L1 scheme or by Convolution Quadrature. We propose new interpretations of the numerical schemes which lead to a posteriori…

Numerical Analysis · Mathematics 2022-03-02 Lehel Banjai , Charalambos G. Makridakis

We consider equidistant approximations of stochastic integrals driven by H\"older continuous Gaussian processes of order $H>\frac12$ with discontinuous integrands involving bounded variation functions. We give exact rate of convergence in…

Probability · Mathematics 2022-09-15 Ehsan Azmoodeh , Pauliina Ilmonen , Nourhan Shafik , Tommi Sottinen , Lauri Viitasaari

We consider the problem of estimating the roughness of the volatility process in a stochastic volatility model that arises as a nonlinear function of fractional Brownian motion with drift. To this end, we introduce a new estimator that…

Statistical Finance · Quantitative Finance 2026-04-17 Xiyue Han , Alexander Schied

We study the approximation of stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H>1/2$. For the mean-square error at a single point we derive the optimal rate of convergence that can be achieved…

Probability · Mathematics 2007-06-19 Andreas Neuenkirch

Holderian functions have strong non-linearities, which result in singularities in the derivatives. This manuscript presents several fractional-order Taylor expansions of H\"olderian functions around points of non- differentiability. These…

Classical Analysis and ODEs · Mathematics 2015-08-26 Dimiter Prodanov

The rate of strong convergence is investigated for an approximation scheme for a class of stochastic differential equations driven by a time-changed Brownian motion, where the random time changes $(E_t)_{t\ge 0}$ considered include the…

Probability · Mathematics 2020-03-02 Sixian Jin , Kei Kobayashi

We discuss a system of stochastic differential equations with a stiff linear term and additive noise driven by fractional Brownian motions (fBms) with Hurst parameter H>1/2, which arise e. g., from spatial approximations of stochastic…

Probability · Mathematics 2024-05-10 Minoo Kamrani , Kristian Debrabant , Nahid Jamshidi

Explicit discretizations of stochastic differential equations often encounter instability when the coefficients are not globally Lipschitz. The truncated schemes and tamed schemes have been proposed to handle this difficulty, but truncated…

Numerical Analysis · Mathematics 2025-07-15 Zichang Ju , Lei Li , Yuliang Wang

Finite difference approximation, in addition to Taylor truncation errors, introduces numerical dispersion-and-dissipation errors into numerical solutions of partial differential equations. We analyze a class of finite difference schemes…

Numerical Analysis · Mathematics 2014-09-12 Yi-Hung Kuo , Long Lee , Gregory Lyng

We consider linear iterative schemes for the time-discrete equations stemming from a class of nonlinear, doubly-degenerate parabolic equations. More precisely, the diffusion is nonlinear and may vanish or become multivalued for certain…

Numerical Analysis · Mathematics 2025-08-12 Ayesha Javed , Koondanibha Mitra , Iuliu Sorin Pop

Real data are constrained to finite sampling rates, which calls for a suitable mathematical description of the corrections to the finite-time estimations of the dynamic equations. Often in the literature, lower order discrete time…

Data Analysis, Statistics and Probability · Physics 2015-05-13 C. Anteneodo , R. Riera