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This paper studies the classification of high-dimensional Gaussian signals from low-dimensional noisy, linear measurements. In particular, it provides upper bounds (sufficient conditions) on the number of measurements required to drive the…

Information Theory · Computer Science 2016-11-03 Hugo Reboredo , Francesco Renna , Robert Calderbank , Miguel R. D. Rodrigues

We construct and derive uniform stochastic estimates on the renormalised model for a class of fourth-order conservative quasilinear singular SPDEs in arbitrary dimension $d\geq 1$ and in the full subcritical regime of noise regularity. The…

Analysis of PDEs · Mathematics 2026-05-19 Rishabh S. Gvalani , Markus Tempelmayr

Semilinear hyperbolic stochastic partial differential equations (SPDEs) find widespread applications in the natural and engineering sciences. However, the traditional Gaussian setting may prove too restrictive, as phenomena in mathematical…

Numerical Analysis · Mathematics 2023-07-04 Andrea Barth , Andreas Stein

We establish a general criterion which ensures exponential mixing of parabolic Stochastic Partial Differential Equations (SPDE) driven by a non additive noise which is white in time and smooth in space. We apply this criterion on two…

Analysis of PDEs · Mathematics 2007-05-23 Cyril Odasso

In many applications, it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite-dimensional analogue…

Probability · Mathematics 2007-11-06 M. Hairer , A. M. Stuart , J. Voss

We give a new take on the error analysis of approximations of stochastic differential equations (SDEs), utilizing and developing the stochastic sewing lemma of L\^e (2020). This approach allows one to exploit regularization by noise effects…

Probability · Mathematics 2021-08-10 Oleg Butkovsky , Konstantinos Dareiotis , Máté Gerencsér

We investigate existence, uniqueness and regularity for local solutions of rough parabolic equations with subcritical noise of the form $du_t- L_tu_tdt= N(u_t)dt + \sum_{i = 1}^dF_i(u_t)d\mathbf X^i_t$ where $(L_t)_{t\in[0,T]}$ is a…

Analysis of PDEs · Mathematics 2021-08-24 Andris Gerasimovics , Antoine Hocquet , Torstein Nilssen

We investigate the optimal H\"older continuity and hitting probabilities for systems of stochastic heat equations and stochastic wave equations driven by an additive fractional Brownian sheet with temporal index $1/2$ and spatial index…

Probability · Mathematics 2022-03-03 Jialin Hong , Zhihui Liu , Derui Sheng

We consider stochastic partial differential equations on $\mathbb{R}^{d}, d\geq 1$, driven by a Gaussian noise white in time and colored in space, for which the pathwise uniqueness holds. By using the Skorokhod representation theorem we…

Probability · Mathematics 2007-05-23 K. Bahlali , M. Eddahbi , M. Mellouk

We consider strong approximations of $1+1$-dimensional stochastic PDEs driven by additive space-time white noise. It has been long proposed (Davie-Gaines '01, Jentzen-Kloeden '08), as well as observed in simulations, that approximation…

Probability · Mathematics 2026-04-17 Ana Djurdjevac , Máté Gerencsér , Helena Kremp

Stochastic differential equations (SDEs) are a staple of mathematical modelling of temporal dynamics. However, a fundamental limitation has been that such models have typically been relatively inflexible, which recent work introducing…

Machine Learning · Computer Science 2021-05-12 Patrick Kidger , James Foster , Xuechen Li , Harald Oberhauser , Terry Lyons

We consider a system of $d$ non-linear stochastic fractional heat equations in spatial dimension $1$ driven by multiplicative $d$-dimensional space-time white noise. We establish a sharp Gaussian-type upper bound on the two-point…

Probability · Mathematics 2018-10-15 Robert C. Dalang , Fei Pu

This article proposes and analyzes explicit and easily implementable temporal numerical approximation schemes for additive noise-driven stochastic partial differential equations (SPDEs) with polynomial nonlinearities such as, e.g.,…

Probability · Mathematics 2021-11-02 Sebastian Becker , Arnulf Jentzen

We study high-probability convergence guarantees of learning on streaming data in the presence of heavy-tailed noise. In the proposed scenario, the model is updated in an online fashion, as new information is observed, without storing any…

Machine Learning · Computer Science 2024-05-02 Aleksandar Armacki , Pranay Sharma , Gauri Joshi , Dragana Bajovic , Dusan Jakovetic , Soummya Kar

This paper focuses on stochastic partial differential equations (SPDEs) under two-time-scale formulation. Distinct from the work in the existing literature, the systems are driven by $\alpha$-stable processes with $\alpha \in(1,2)$. In…

Statistics Theory · Mathematics 2016-09-30 Jianhai Bao , George Yin , Chenggui Yuan

An empirical Bayes approach to the estimation of possibly sparse sequences observed in Gaussian white noise is set out and investigated. The prior considered is a mixture of an atom of probability at zero and a heavy-tailed density \gamma,…

Statistics Theory · Mathematics 2007-06-13 Iain M. Johnstone , Bernard W. Silverman

We study strictly parabolic stochastic partial differential equations on $\R^d$, $d\ge 1$, driven by a Gaussian noise white in time and coloured in space. Assuming that the coefficients of the differential operator are random, we give…

Probability · Mathematics 2007-05-23 Marco Ferrante , Marta Sanz-Solé

We consider a system of $d$ coupled non-linear stochastic heat equations in spatial dimension 1 driven by $d$-dimensional additive space-time white noise. We establish upper and lower bounds on hitting probabilities of the solution $\{u(t,…

Probability · Mathematics 2007-05-23 Robert C. Dalang , Davar Khoshnevisan , Eulalia Nualart

We consider identifiability of partially linear additive structural equation models with Gaussian noise (PLSEMs) and estimation of distributionally equivalent models to a given PLSEM. Thereby, we also include robustness results for errors…

Statistics Theory · Mathematics 2017-12-15 Dominik Rothenhäusler , Jan Ernest , Peter Bühlmann

The concept of time-correlated noise is important to applied stochastic modelling. Nevertheless, there is no generally agreed-upon definition of the term red noise in continuous-time stochastic modelling settings. We present here a rigorous…

Probability · Mathematics 2025-08-14 Andreas Morr , Dörte Kreher , Niklas Boers