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In this article, we introduce a system of stochastic differential equations (SDEs) consisting of time-dependent covariates and consider both fixed and random effects set-ups. We also allow the functional part associated with the drift…

Statistics Theory · Mathematics 2017-10-16 Trisha Maitra , Sourabh Bhattacharya

We study parabolic stochastic partial differential equations (SPDEs), driven by two types of operators: one linear closed operator generating a $C_0-$semigroup and one linear bounded operator with Wick-type multiplication, all of them set…

Probability · Mathematics 2023-03-16 Tijana Levajkovic , Stevan Pilipovic , Dora Selesi , Milica Zigic

This paper presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in geostatistics. We show a general approach to construct stationary models related to a wide class of linear SPDEs,…

Statistics Theory · Mathematics 2018-07-30 Ricardo Carrizo Vergara , Denis Allard , Nicolas Desassis

We study the problem of learning the law of linear stochastic partial differential equations (SPDEs) with additive Gaussian forcing from spatiotemporal observations. Most existing deep learning approaches either assume access to the driving…

Machine Learning · Computer Science 2026-02-13 Sebastian Zeng , Andreas Petersson , Wolfgang Bock

Probabilistic ordinary differential equation (ODE) solvers have been introduced over the past decade as uncertainty-aware numerical integrators. They typically proceed by assuming a functional prior to the ODE solution, which is then…

Numerical Analysis · Mathematics 2025-03-25 Yvann Le Fay , Simo Särkkä , Adrien Corenflos

Three-wave interactions (or resonant triads) are the lowest-order nonlinear interaction in pattern formation and arise between waves with different orientations when the sum of two wavevectors equals a third one. When a pattern has only one…

Pattern Formation and Solitons · Physics 2026-05-26 Laura Pinkney , Alastair M. Rucklidge , Cedric Beaume

In this study we discuss the shapes and statistics of the rogue (freak) waves emerging due to wave-current interactions. With this purpose, we use a simple governing equation which is a nonlinear Schrodinger equation (NLSE) extended by R.…

Chaotic Dynamics · Physics 2015-12-14 Cihan Bayindir

This paper derives stochastic partial differential equations (SPDEs) for fluid dynamics from a stochastic variational principle (SVP). The Legendre transform of the Lagrangian formulation of these SPDEs yields their Lie-Poisson Hamiltonian…

Mathematical Physics · Physics 2015-08-19 Darryl D. Holm

A stochastic wavevector approach is formulated to accurately represent compressible turbulence subject to rapid deformations. This approach is inspired by the incompressible particle representation model of Kassinos (1995) and preserves the…

Fluid Dynamics · Physics 2025-01-30 Noah Zambrano , Karthik Duraisamy

We determine the modulational stability of standing waves with small group velocity in quasi-onedimensional systems slightly above the threshold of a supercritical Hopf bifurcation. The stability limits are given by two different…

patt-sol · Physics 2009-09-25 Hermann Riecke , Lorenz Kramer

A well-known optimal velocity (OV) model describes vehicle motion along a single lane road, which reduces to a perturbed modified Korteweg-de Vries (mKdV) equation within the unstable regime. Steady travelling wave solutions to this…

Dynamical Systems · Mathematics 2016-08-12 Laura Hattam

Stochastic differential equations (SDEs) provide a flexible framework for modeling temporal dynamics in partially observed systems. A central task is to calibrate such models from data, which requires inferring latent trajectories and…

Machine Learning · Statistics 2026-05-08 Yu Wang , Arnab Ganguly

Robust physics (e.g., governing equations and laws) discovery is of great interest for many engineering fields and explainable machine learning. A critical challenge compared with general training is that the term and format of governing…

Numerical Analysis · Mathematics 2021-02-15 Zhiming Zhang , Yongming Liu

In this paper we focus on a discrete physical model describing granular crystals, whose equations of motion can be described by a system of differential difference equations (DDEs). After revisiting earlier continuum approximations, we…

Pattern Formation and Solitons · Physics 2025-07-08 Su Yang , Gino Biondini , Christopher Chong , Panayotis G. Kevrekidis

In this note we introduce a new approach to rough and stochastic partial differential equations (RPDEs and SPDEs): we consider general Banach spaces as state spaces and -- for the sake of simiplicity -- finite dimensional sources of noise,…

Probability · Mathematics 2009-08-21 Josef Teichmann

It has been reported that traveling waves propagate periodically and stably in sub-excitable systems driven by noise [Phys. Rev. Lett. \textbf{88}, 138301 (2002)]. As a further investigation, here we observe different types of traveling…

Chaotic Dynamics · Physics 2008-01-17 Fen-Ni Si , Quan-Xing Liu , Jin-Zhong Zhang , Lu-Qun Zhou

The streamwise roll and streak structure (RSS) is prominent in observations of the planetary boundary layer in the atmosphere and ocean and in unstratified wall-bounded shear flows. Although the RSS in these systems is structurally similar,…

Fluid Dynamics · Physics 2025-06-16 Eojin Kim , Brian F. Farrell

The dynamics of pseudo-classical spinning particles in spacetime of gravitational plane waves of general polarization and harmonic profile is studied. The resulting equations of motion are solved exactly and the results are compared with…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Morteza Mohseni

The nonlinear Schroedinger equation possesses three distinct six-parameter families of complex-valued quasi-periodic travelling waves, one in the defocusing case and two in the focusing case. All these solutions have the property that their…

Analysis of PDEs · Mathematics 2007-05-23 Thierry Gallay , Mariana Haragus

Stochastic Partial Differential Equations (SPDEs) driven by random noise play a central role in modeling physical processes with rough spatio-temporal dynamics, such as turbulence flows, superconductors, and quantum dynamics. Although…

Machine Learning · Computer Science 2026-05-18 Yuantu Zhu , Zheyan Li , Dai Shi , Luke Thompson , Oliver Nash , Jose Miguel Lara Rangel , Siran Li , Bingguang Chen , Rongchan Zhu , Qi Meng , Hao Ni
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