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We prove gradient bounds for the Markov semigroup of the dynamic $\varphi^4_2$-model on a torus of fixed size $L>0$. For sufficiently large mass $m>0$ these estimates imply exponential contraction of the Markov semigroup. Our method is…

Probability · Mathematics 2022-02-23 Florian Kunick , Pavlos Tsatsoulis

We present a novel model Graph Neural Stochastic Differential Equations (Graph Neural SDEs). This technique enhances the Graph Neural Ordinary Differential Equations (Graph Neural ODEs) by embedding randomness into data representation using…

Machine Learning · Computer Science 2023-08-25 Richard Bergna , Felix Opolka , Pietro Liò , Jose Miguel Hernandez-Lobato

We study a class of stochastic evolution equations with a dissipative forcing nonlinearity and additive noise. The noise is assumed to satisfy rather general assumptions about the form of the covariance function; our framework covers…

Probability · Mathematics 2009-11-23 Stefano Bonaccorsi , Ciprian Tudor

In this thesis, we extend the recently introduced theory of stochastic modified equations (SMEs) for stochastic gradient optimization algorithms. In Ch. 3 we study time-inhomogeneous SDEs driven by Brownian motion. For certain SDEs we prove…

Probability · Mathematics 2025-11-26 Stefan Perko

The main goal of this paper is to study the parameter estimation problem, using the Bayesian methodology, for the drift coefficient of some linear (parabolic) SPDEs driven by a multiplicative noise of special structure. We take the spectral…

Statistics Theory · Mathematics 2019-03-05 Ziteng Cheng , Igor Cialenco , Ruoting Gong

In this paper, we study averaging principle for a class of McKean-Vlasov stochastic differential equations (SDEs) that contain multiplicative fractional noise with Hurst parameter $H > $ 1/2 and highly oscillatory drift coefficient. Here…

Probability · Mathematics 2023-06-06 Bin Pei , Lifang Feng , Min Han

By solving a control problem and using Malliavin calculus, explicit derivative formula is derived for the semigroup $P_t$ generated by the Gruschin type operator on $\R^{m}\times \R^{d}:$ $$L (x,y)=\ff 1 2 \bigg\{\sum_{i=1}^m \pp_{x_i}^2…

Probability · Mathematics 2013-04-04 Feng-Yu Wang

We investigate, in the setting of UMD Banach spaces E, the continuous dependence on the data A, F, G and X_0 of mild solutions of semilinear stochastic evolution equations with multiplicative noise of the form dX(t) = [AX(t) + F(t,X(t))]dt…

Probability · Mathematics 2011-02-10 Markus Kunze , Jan van Neerven

We consider stochastic partial differential equations (SPDEs) on the one-dimensional torus, driven by space-time white noise, and with a time-periodic drift term, which vanishes on two stable and one unstable equilibrium branches. Each of…

Probability · Mathematics 2024-02-27 Nils Berglund , Rita Nader

In recent years, an intensive study of strong approximation of stochastic differential equations (SDEs) with a drift coefficient that may have discontinuities in space has begun. In many of these results it is assumed that the drift…

Probability · Mathematics 2021-03-01 Larisa Yaroslavtseva

In this paper we establish the strong existence, pathwise uniqueness and a comparison theorem to a stochastic partial differential equation driven by Gaussian colored noise with non-Lipschitz drift, H\"older continuous diffusion…

Probability · Mathematics 2020-06-02 Jie Xiong , Xu Yang

By using the Malliavin calculus and finite-jump approximations, the Driver-type integration by parts formula is established for the semigroup associated to stochastic differential equations with noises containing a subordinate Brownian…

Probability · Mathematics 2013-08-28 Feng-Yu Wang

Let $d\geq 2$. In this paper, we investigate the following stochastic differential equation (SDE) in ${\mathbb R}^d$ driven by Brownian motion $$ {\rm d} X_t=b(t,X_t){\rm d} t+\sqrt{2}{\rm d} W_t, $$ where $b$ belongs to the space ${\mathbb…

Probability · Mathematics 2025-08-05 Zimo Hao , Xicheng Zhang

We consider a stochastic partial differential equation (SPDE) model for chemorepulsion, with non-linear sensitivity on the one-dimensional torus. We show that for any suitable initial data there exists a pathwise unique, global solution to…

Probability · Mathematics 2023-08-22 Ilya Chevyrev , Ben Hambly , Avi Mayorcas

We derive an asymptotic log-Harnack inequality for nonlinear monotone SPDE driven by possibly degenerate multiplicative noise. Our main tool is the asymptotic coupling by the change of measure. As an application, we show that, under certain…

Probability · Mathematics 2024-09-19 Zhihui Liu

Asymptotic expansions are derived as power series in a small coefficient entering a nonlinear multiplicative noise and a deterministic driving term in a nonlinear evolution equation. Detailed estimates on remainders are provided.

Probability · Mathematics 2013-12-10 Sergio Albeverio , Boubaker Smii

By using absolutely continuous lower bounds of the L\'evy measure, explicit gradient estimates are derived for the semigroup of the corresponding L\'evy process with a linear drift. A derivative formula is presented for the conditional…

Probability · Mathematics 2011-03-16 Feng-Yu Wang

In this paper, we establish the existence and uniqueness of invariant measures for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results can be applied to SPDEs…

Probability · Mathematics 2018-12-12 Zhao Dong , Rangrang Zhang

We study a new class of McKean-Vlasov stochastic differential equations (SDEs), possibly with common noise, applying the theory of time-inhomogeneous polynomial processes. The drift and volatility coefficients of these SDEs depend on the…

Probability · Mathematics 2025-02-27 Christa Cuchiero , Janka Möller

The solution of a parabolic stochastic partial differential equation (SPDE) driven by an infinite-dimensional Brownian motion is in general not a semi-martingale anymore and does in general not satisfy an It\^{o} formula like the solution…

Probability · Mathematics 2010-10-04 Arnulf Jentzen , Peter Kloeden