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The Gromov-Wasserstein (GW) distance quantifies discrepancy between metric measure spaces and provides a natural framework for aligning heterogeneous datasets. Alas, as exact computation of GW alignment is NP hard, entropic regularization…

Optimization and Control · Mathematics 2024-01-11 Gabriel Rioux , Ziv Goldfeld , Kengo Kato

We consider nonlinear parabolic evolution equations of the form $\partial_{t}u=F(t,x,Du,D^{2}u) $, subject to noise of the form $H(x,Du) \circ dB$ where $H$ is linear in $Du$ and $\circ dB$ denotes the Stratonovich differential of a…

Analysis of PDEs · Mathematics 2010-11-09 Michael Caruana , Peter Friz , Harald Oberhauser

This paper studies finite element approximations of the stochastic Allen-Cahn equation with gradient-type multiplicative noises that are white in time and correlated in space. The sharp interface limit as the parameter $\epsilon \rightarrow…

Numerical Analysis · Mathematics 2015-05-18 Xiaobing Feng , Yukun Li , Yi Zhang

We develop a path integral framework for determining most probable paths in a class of systems of stochastic differential equations with piecewise-smooth drift and additive noise. This approach extends the Freidlin-Wentzell theory of large…

Dynamical Systems · Mathematics 2022-11-08 Kaitlin Hill , Jessica Zanetell , John A Gemmer

We prove the strong completeness for a class of non-degenerate SDEs, whose coefficients are not necessarily uniformly elliptic nor locally Lipschitz continuous nor bounded. Moreover, for each $t$, the solution flow $F_t$ is weakly…

Probability · Mathematics 2016-05-09 Xin Chen , Xue-Mei Li

Elliptic stochastic differential equations (SDE) make sense when the coefficients are only continuous. We study the corresponding linearized SDE whose coefficients are not assumed to be locally bounded. This leads to existence of…

Probability · Mathematics 2010-08-09 Xin Chen , Xue-Mei Li

We consider a method for the approximation of iterated stochastic integrals of arbitrary multiplicity $k$ $(k\in \mathbb{N})$ with respect to the infinite-dimensional $Q$-Wiener process using the mean-square approximation method of iterated…

General Mathematics · Mathematics 2022-03-15 Dmitriy F. Kuznetsov

We continue the development of the theory of pathwise stochastic entropy solutions for scalar conservation laws in $\R^N$ with quasilinear multiplicative ''rough path'' dependence by considering inhomogeneous fluxes and a single rough path…

Analysis of PDEs · Mathematics 2014-04-07 Pierre-Louis Lions , Benoit Perthame , Panagiotis E. Souganidis

We study the statistical inference of nonlinear stochastic approximation algorithms utilizing a single trajectory of Markovian data. Our methodology has practical applications in various scenarios, such as Stochastic Gradient Descent (SGD)…

Statistics Theory · Mathematics 2023-02-21 Xiang Li , Jiadong Liang , Zhihua Zhang

These are lecture notes for a Master 2 course on rough differential equations driven by weak geometric Holder p-rough paths, for any p>2. They provide a short, self-contained and pedagogical account of the theory, with an emphasis on flows.…

Classical Analysis and ODEs · Mathematics 2014-04-04 Ismael Bailleul

We develop a Fourier approach to rough path integration, based on the series decomposition of continuous functions in terms of Schauder functions. Our approach is rather elementary, the main ingredient being a simple commutator estimate,…

Probability · Mathematics 2014-10-16 Massimiliano Gubinelli , Peter Imkeller , Nicolas Perkowski

In this article, we present a general methodology for stochastic control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state processes controlled by mutually singular measures. The main…

Probability · Mathematics 2024-04-04 Dorival Leão , Alberto Ohashi , Francys Andrews de Souza

In this paper, we investigate a semilinear stochastic parabolic equation with a linear rough term $du_{t}=\left[L_{t}u_{t}+f\left(t, u_{t}\right)\right]dt+\left(G_{t}u_{t}+g_{t}\right)d\mathbf{X}_{t}+h\left(t, u_{t}\right)dW_{t}$, where…

Probability · Mathematics 2024-01-31 Jiahao Liang , Shanjian Tang

Consider additive functionals of a Markov chain $W_k$, with stationary (marginal) distribution and transition function denoted by $\pi$ and $Q$, say $S_n=g(W_1)+...+g(W_n)$, where $g$ is square integrable and has mean 0 with respect to…

Probability · Mathematics 2008-11-14 Ou Zhao , Michael Woodroofe

We present a systematic approach for the semiclassical treatment of many-body dynamics of interacting, open spin systems. Our approach overcomes some of the shortcomings of the recently developed discrete truncated Wigner approximation…

Quantum Physics · Physics 2022-12-01 Christopher D. Mink , David Petrosyan , Michael Fleischhauer

This paper is devoted to the study of the stochastic fixed-point equation X \stackrel{d}{=} \inf_{i \geq 1: T_i > 0} X_i/T_i and the connection with its additive counterpart $X \stackrel{d}{=} \sum_{i\ge 1}T_{i}X_{i}$ associated with the…

Probability · Mathematics 2010-03-18 Gerold Alsmeyer , Matthias Meiners

We deal with the problem of gradient estimation for stochastic differentiable relaxations of algorithms, operators, simulators, and other non-differentiable functions. Stochastic smoothing conventionally perturbs the input of a…

Machine Learning · Computer Science 2024-10-11 Felix Petersen , Christian Borgelt , Aashwin Mishra , Stefano Ermon

Consider a multidimensional diffusion process $X=\{X\left(t\right) :t\in\lbrack0,1]\}$. Let $\varepsilon>0$ be a \textit{deterministic}, user defined, tolerance error parameter. Under standard regularity conditions on the drift and…

Probability · Mathematics 2016-07-22 Jose Blanchet , Xinyun Chen , Jing Dong

A 2D Stochastic incompressible non-Newtonian fluids driven by fractional Bronwnian motion with Hurst parameter $H \in (1/2,1)$ is studied. The Wiener-type stochastic integrals are introduced for infinite-dimensional fractional Brownian…

Mathematical Physics · Physics 2011-07-15 Jin Li , Jianhua Huang

We are concerned with a mixture of Boltzmann and McKean-Vlasov type equations, this means (in probabilistic terms) equations with coefficients depending on the law of the solution itself,and driven by a Poisson point measure with the…

Probability · Mathematics 2021-05-27 Aurélien Alfonsi , Vlad Bally