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Related papers: Rough flows

200 papers

A Gaussian process (GP)-based methodology is proposed to emulate complex dynamical computer models (or simulators). The method relies on emulating the numerical flow map of the system over an initial (short) time step, where the flow map is…

Methodology · Statistics 2024-11-26 Hossein Mohammadi , Peter Challenor , Marc Goodfellow

We investigate a family of approximate multi-step proximal point methods, accelerated by implicit linear discretizations of gradient flow. The resulting methods are multi-step proximal point methods, with similar computational cost in each…

Optimization and Control · Mathematics 2023-10-23 Yushen Huang , Yifan Sun

We survey existing results concerning the study in small times of the density of the solution of a rough differential equation driven by fractional Brownian motions. We also slightly improve existing results and discuss some possible…

Probability · Mathematics 2014-03-05 Fabrice Baudoin , Cheng Ouyang

This is a survey article on Morse theory based on lectures to graduate students and advanced undergraduates. After a brief review of standard material, mostly without proofs, the Morse theory of complex Grassmannian manifolds is worked out…

Differential Geometry · Mathematics 2007-05-23 Martin Guest

Stochastic network calculus is a newly developed theory for stochastic service guarantee analysis of computer networks. In the current stochastic network calculus literature, its fundamental models are based on the cumulative amount of…

Performance · Computer Science 2011-12-14 Jing Xie , Yuming Jiang , Min Xie

Whenever an It\^o-Wentsel type of formula holds for composition of flows of a certain differential dynamics, there exists locally a decomposition of the corresponding flow according to complementary distributions (or foliations, in the case…

Probability · Mathematics 2022-12-20 Pedro Catuogno , Lourival Lima , Paulo Ruffino

This work establishes the existence and regularity of random pullback attractors for parabolic partial differential equations with rough nonlinear multiplicative noise under natural assumptions on the coefficients. To this aim, we combine…

Probability · Mathematics 2024-01-26 Alexandra Neamtu , Tim Seitz

This paper introduces a method to approximate Gaussian process regression by representing the problem as a stochastic differential equation and using variational inference to approximate solutions. The approximations are compared with full…

Machine Learning · Computer Science 2019-01-08 Wil O C Ward , Mauricio A Álvarez

We derive explicit tail-estimates for the Jacobian of the solution flow for stochastic differential equations driven by Gaussian rough paths. In particular, we deduce that the Jacobian has finite moments of all order for a wide class of…

Probability · Mathematics 2013-07-26 Thomas Cass , Christian Litterer , Terry Lyons

We introduce one-way flows in near algebras and two-way flows in double near algebras with two interrelated multiplications. We establish parametric representations of the one-way and two-way flows in terms of a single element of the…

Rings and Algebras · Mathematics 2022-11-17 Włodzimierz Bryc , Jacek Wesołowski , Agnieszka Zięba

We use a version of the Trotter-Kato approximation theorem for strongly continuous semigroups in order to study flows on growing networks. For that reason we use the abstract notion of direct limits in the sense of category theory.

Analysis of PDEs · Mathematics 2021-02-25 Christian Budde

The evolution by horizontal mean curvature flow (HMCF) is a partial differential equation in a sub-Riemannian setting with application in IT and neurogeometry (see Citti-Franceschiello-Sanguinetti-Sarti, 2016). Unfortunately this equation…

Analysis of PDEs · Mathematics 2021-05-14 Raffaele Grande

The two phase model for vehicular traffic flows recently appeared in \cite{goatin2006aw} and \cite{BenyahiaRosini01} is endowed with a point constraint on the flow to allow for the modelling of phenomena such as the effects of toll booths…

Analysis of PDEs · Mathematics 2016-05-27 Massimiliano D. Rosini , Benyahia Mohamed Ramiz

In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point clouds as continuous probability density functions using…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Pan He , Patrick Emami , Sanjay Ranka , Anand Rangarajan

This is a set of four lectures devoted to simple ideas about turbulent transport, a ubiquitous non-equilibrium phenomenon. In the course similar to that given by the author in 2006 in Warwick [45], we discuss lessons which have been learned…

Chaotic Dynamics · Physics 2008-06-12 Krzysztof Gawedzki

Here we carry out computations that help clarify the Lagrangian and Hamiltonian structure of compressible flow. The intent is to be pedagogical and rigorous, providing concrete examples of the theory outlined in Holm, Marsden, and Ratiu…

Mathematical Physics · Physics 2007-05-23 H. S. Bhat

This paper introduces the path derivatives, in the spirit of Dupire's functional It\^o calculus, for the controlled paths in the rough path theory with possibly non-geometric rough paths. The theory allows us to deal with rough integration…

Probability · Mathematics 2014-12-24 Christian Keller , Jianfeng Zhang

Using fractional calculus we define integrals of the form $% \int_{a}^{b}f(x_{t})dy_{t}$, where $x$ and $y$ are vector-valued H\"{o}lder continuous functions of order $\displaystyle \beta \in (\frac13, \frac12)$ and $f$ is a continuously…

Probability · Mathematics 2007-05-23 Yaozhong Hu , David Nualart

This paper proposes a theoretical framework for modeling and optimizing the bounded functions based on the Fourier series approximation and Ricci flow. Specifically, the initial manifold, $\mathcal{M}_0$ is approximated using Fourier series…

Differential Geometry · Mathematics 2025-03-13 Varsha Gupta

We introduce a stochastic traffic flow model to describe random traffic accidents on a single road. The model is a piecewise deterministic process incorporating traffic accidents and is based on a scalar conservation law with…

Probability · Mathematics 2019-12-13 Simone Göttlich , Stephan Knapp