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Related papers: Path-dependent rough differential equations

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An adaptive model for the description of flows in highly heterogeneous porous media is developed in~\cite{FP21,FP23}. There, depending on the magnitude of the fluid's velocity, the constitutive law linking velocity and pressure gradient is…

Numerical Analysis · Mathematics 2024-05-06 Alessio Fumagalli , Francesco S. Patacchini

Given a one-dimensional stochastic differential equation, one can associate to this equation a stochastic flow on $[0,+\infty )$, which has an absorbing barrier at zero. Then one can define its dual stochastic flow. In \cite{AW}, Akahori…

Probability · Mathematics 2015-09-01 Takafumi Amaba , Dai Taguchi , Go Yuki

We prove well-posedness and rough path stability of a class of linear and semi-linear rough PDE's on $\mathbb{R}^d$ using the variational approach. This includes well-posedness of (possibly degenerate) linear rough PDE's in…

Probability · Mathematics 2020-01-13 Peter Friz , Torstein Nilssen , Wilhelm Stannat

We give faster algorithms for weak expander decompositions and approximate max flow on undirected graphs. First, we show that it is possible to "warm start" the cut-matching game when computing weak expander decompositions, avoiding the…

Data Structures and Algorithms · Computer Science 2025-11-06 Henry Fleischmann , George Z. Li , Jason Li

In this work we study rough differential equations driven by a fractional Brownian motion with Hurst parameter H>1/4 and establish Varadhan's small time estimates for the density of solutions of such equations under Hormander's type…

Probability · Mathematics 2013-04-30 Fabrice Baudoin , Cheng Ouyang , Xuejing Zhang

Real world networks are often subject to severe uncertainties which need to be addressed by any reliable prescriptive model. In the context of the maximum flow problem subject to arc failure, robust models have gained particular attention.…

Discrete Mathematics · Computer Science 2017-05-24 Fabian Mies , Britta Peis , Andreas Wierz

This paper is devoted to the study of weak and strong convergence of derivations, and of the flows associated to them, when dealing with a sequence of metric measure structures (X,d,m_n), m_n weakly convergent to m. In particular, under…

Metric Geometry · Mathematics 2016-10-17 Luigi Ambrosio , Federico Stra , Dario Trevisan

Solving large complex partial differential equations (PDEs), such as those that arise in computational fluid dynamics (CFD), is a computationally expensive process. This has motivated the use of deep learning approaches to approximate the…

Machine Learning · Computer Science 2020-08-18 Filipe de Avila Belbute-Peres , Thomas D. Economon , J. Zico Kolter

This paper is devoted to the smooth and stationary Wong-Zakai approximations for a class of rough differential equations driven by a geometric fractional Brownian rough path $\boldsymbol{\omega}$ with Hurst index…

Probability · Mathematics 2023-03-09 Qiyong Cao , Hongjun Gao , Bjorn Schmalfuss

Many dynamical systems can be described in terms of structured flows combining source/sink behavior, cyclic dynamics, and topology-constrained transport. These features arise across a wide range of domains, including physical, engineered,…

Data Analysis, Statistics and Probability · Physics 2026-05-19 Diego Casadei

This work presents mixed variational flows (MixFlows), a new variational family that consists of a mixture of repeated applications of a map to an initial reference distribution. First, we provide efficient algorithms for i.i.d. sampling,…

Machine Learning · Statistics 2025-06-03 Zuheng Xu , Naitong Chen , Trevor Campbell

We explore a link between stochastic volatility (SV) and path-dependent volatility (PDV) models. Using assumed density filtering, we map a given SV model into a corresponding PDV representation. The resulting specification is lightweight,…

Mathematical Finance · Quantitative Finance 2025-10-03 Samuel N. Cohen , Cephas Svosve

A branched rough path $X$ consists of a rough integral calculus for $X \colon [0, T] \to \mathbb R^d$ which may fail to satisfy integration by parts. Using Kelly's bracket extension [Kel12], we define a notion of pushforward of branched…

Classical Analysis and ODEs · Mathematics 2023-11-29 Emilio Ferrucci

This paper shows that the topological structures of particle orbits generated by a generic class of vector fields on spherical surfaces, called {\it the flow of finite type}, are in one-to-one correspondence with discrete structures such as…

Dynamical Systems · Mathematics 2022-08-18 Takashi Sakajo , Tomoo Yokoyama

Charge dependent directed flow is an important observable of electromagnetic fields in relativistic heavy-ion collisions. We demonstrate how the difference in charge dependent directed flows between protons and antiprotons is sensitive to…

Nuclear Theory · Physics 2025-08-25 Nicholas J. Benoit , Takahiro Miyoshi , Chiho Nonaka , Hiroyuki R. Takahashi

In 2015, Bailleul presented a mechanism to solve rough differential equations by constructing flows, using the log-ODE method. We extend this notion in two ways: On the one hand, we localize Bailleul's notion of an almost-flow to solve RDEs…

Probability · Mathematics 2023-12-19 Hannes Kern , Terry Lyons

The use of adaptive spatial resolution to simulate flows of practical interest using Smoothed Particle Hydrodynamics (SPH) is of considerable importance. Recently, Muta and Ramachandran [1] have proposed an efficient adaptive SPH method…

Fluid Dynamics · Physics 2022-05-17 Asmelash Haftu , Abhinav Muta , Prabhu Ramachandran

Existence and uniqueness for rough flows, transport and continuity equations driven by general geometric rough paths are established.

Analysis of PDEs · Mathematics 2021-10-05 Carlo Bellingeri , Ana Djurdjevac , Peter K. Friz , Nikolas Tapia

The theory of rough paths arose from a desire to establish continuity properties of ordinary differential equations involving terms of low regularity. While essentially an analytic theory, its main motivation and applications are in…

Classical Analysis and ODEs · Mathematics 2025-01-28 Ilya Chevyrev

We prove that solutions of stochastic differential equations driven by fractional Brownian motion for $H>1/2$ define flows of homeomorphisms on $\mathbb{R}^{d}$.

Probability · Mathematics 2007-05-23 L. Decreusefond , D. Nualart
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