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Introducing inequality constraints in Gaussian process (GP) models can lead to more realistic uncertainties in learning a great variety of real-world problems. We consider the finite-dimensional Gaussian approach from Maatouk and Bay (2017)…

Machine Learning · Statistics 2021-11-04 Andrés F. López-Lopera , François Bachoc , Nicolas Durrande , Olivier Roustant

We consider marked point processes on the d-dimensional euclidean space, defined in terms of a quasilocal specification based on marked Poisson point processes. We investigate the possibility of constructing absolutely-summable Hamiltonians…

Probability · Mathematics 2018-10-30 Benedikt Jahnel , Christof Külske

Recent advances in infinite-dimensional diffusion models have demonstrated their effectiveness and scalability in function generation tasks where the underlying structure is inherently infinite-dimensional. To accelerate inference in such…

Machine Learning · Computer Science 2025-03-14 Kunwoo Na , Junghyun Lee , Se-Young Yun , Sungbin Lim

In this paper, we study a very general stochastic variational inequality(SVI) having jumps, random coefficients, delay, and path dependence, in infinite dimensions. Well-posedness in terms of the existence and uniqueness of a solution is…

Probability · Mathematics 2024-08-16 Ning Ning , Jing Wu , Xiaoyan Xu

We develop several aspects of the infinite-dimensional Weak KAM theory using a random variables' approach. We prove that the infinite-dimensional cell problem admits a viscosity solution that is a fixed point of the Lax-Oleinik semigroup.…

Dynamical Systems · Mathematics 2015-08-04 Diogo Gomes , Levon Nurbekyan

Much effort has been spent in recent years on restoring uniqueness of McKean-Vlasov SDEs with non-smooth coefficients. As a typical instance, the velocity field is assumed to be bounded and measurable in its space variable and…

Probability · Mathematics 2020-02-25 Victor Marx

We review recent progress in the study of infinite-dimensional stochastic differential equations with symmetry. This paper contains examples arising from random matrix theory.

Probability · Mathematics 2017-01-17 Hirofumi Osada

We solve the infinite-dimensional stochastic differential equations (ISDEs) describing an infinite number of Brownian particles in $ \mathbb{R}^+$ interacting through the two-dimensional Coulomb potential. The equilibrium states of the…

Probability · Mathematics 2015-05-12 Ryuich Honda , Hirofumi Osada

In this paper, we study diagonalizable hyperbolic systems in one space dimension. Based on a new gradient entropy estimate, we prove the global existence of a continuous solution, for large and nondecreasing initial data. Moreover, we show…

Mathematical Physics · Physics 2008-12-18 Ahmad El Hajj , Regis Monneau

We consider an infinite-dimensional dynamical system with polynomial nonlinearity and additive noise given by a finite number of Wiener processes. By studying how randomness is spread by the system we develop a counterpart of Hormander's…

Probability · Mathematics 2007-05-23 Yuri Bakhtin , Jonathan C. Mattingly

In this paper, we study ergodic backward stochastic differential equations (EBSDEs for short), for which the underlying diffusion is assumed to be multiplicative and of at most linear growth. The fact that the forward process has an…

Probability · Mathematics 2018-01-08 Ying Hu , Florian Lemonnier

This paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear…

Numerical Analysis · Mathematics 2025-06-06 Daozhe Lin , Qiang Du

In this study, we concern the multidimensional viscosity solutions theory of a kind of semi-linear partial differential equations (PDEs). A new definition of viscosity solution for this multidimensional semi-linear PDEs which is related to…

Dynamical Systems · Mathematics 2016-08-09 Shuzhen Yang

In this paper we extend the definition of time conditional G-expectations $\mathbb{\hat{E}}_{t}[\cdot]$ to a larger domain on which the dynamical consistency still holds. In fact we can consistently define, by taking the limit, the time…

Probability · Mathematics 2013-09-17 Mingshang Hu , Shige Peng

The infinitely-many-neutral-alleles model has recently been extended to a class of diffusion processes associated with Gibbs partitions of two-parameter Poisson-Dirichlet type. This paper introduces a family of infinite-dimensional…

Probability · Mathematics 2013-02-15 Matteo Ruggiero , Stephen G. Walker , Stefano Favaro

Distribution dependent stochastic differential equations have been a very hot subject with extensive studies. On the other hand, under the $G$-expectation framework, stochastic differential equations driven by $G$-Brownian motion (in short…

Probability · Mathematics 2023-02-27 De Sun , Jiang-Lun Wu , Panyu Wu

We consider a scalar, possibly degenerate parabolic equation with a source term, in several space dimensions. For initial data with bounded variation we prove the existence of solutions to the initial-value problem. Then we show that these…

Analysis of PDEs · Mathematics 2018-01-08 Giuseppe Coclite , Andrea Corli , Lorenzo di Ruvo

This note deals with existence and uniqueness of (variational) solutions to the following type of stochastic partial differential equations on a Hilbert space H dX(t) = A(t,X(t))dt + B(t,X(t))dW(t) + h(t) dG(t) where A and B are random…

Probability · Mathematics 2018-06-18 Michael Röckner , Yi Wang

We present an approach to cosmological perturbations based on a covariant perturbative expansion between two worldlines in the real inhomogeneous universe. As an application, at an arbitrary order we define an exact scalar quantity which…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Kari Enqvist , Janne Hogdahl , Sami Nurmi , Filippo Vernizzi

To quantify uncertainties in inverse problems of partial differential equations (PDEs), we formulate them into statistical inference problems using Bayes' formula. Recently, well-justified infinite-dimensional Bayesian analysis methods have…

Numerical Analysis · Mathematics 2026-02-09 Junxiong Jia , Yanni Wu , Peijun Li , Deyu Meng