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Related papers: A Causal Construction of Diffusion Processes

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Causal effect estimation is important for many tasks in the natural and social sciences. We design algorithms for the continuous partial identification problem: bounding the effects of multivariate, continuous treatments when unmeasured…

Machine Learning · Statistics 2023-05-18 Kirtan Padh , Jakob Zeitler , David Watson , Matt Kusner , Ricardo Silva , Niki Kilbertus

The concept of the derivative-dependent functional separable solution, as a generalization to the functional separable solution, is proposed. As an application, it is used to discuss the generalized nonlinear diffusion equations based on…

Exactly Solvable and Integrable Systems · Physics 2009-11-07 Shun-li Zhang , Sen-yue Lou , Chang-zheng Qu

The nonlinear diffusion in multicomponent liquids under chemical reactions influence has been studied. The theory is applied to the analysis of mass transfer in a solution of acetone-benzene. It has been shown, that the creation of…

Fluid Dynamics · Physics 2010-05-20 Vjacheslav V. Obukhovsky , Viktoriya V. Nikonova

The unified description of diffusion processes that cross over from a ballistic behavior at short times to normal or anomalous diffusion (sub- or superdiffusion) at longer times is constructed on the basis of a non-Markovian generalization…

Statistical Mechanics · Physics 2013-03-26 Valery Ilyin , Itamar Procaccia , Anatoly Zagorodny

In this work a method is presented to derive the generating functional in path integral form for a system with an arbitrary number of degrees of freedom and constrained by general conditions. The method is applied to the case of the…

Statistical Mechanics · Physics 2015-05-30 Franco Ferrari

This overview article concerns the notion of fractional smoothness of random variables of the form $g(X_T)$, where $X=(X_t)_{t\in [0,T]}$ is a certain diffusion process. We review the connection to the real interpolation theory, give…

Probability · Mathematics 2010-04-22 Stefan Geiss , Emmanuel Gobet

The linearization principle states that the stability (or instability) of solutions to a suitable linearization of a nonlinear problem implies the stability (or instability) of solutions to the original nonlinear problem. In this work, we…

Analysis of PDEs · Mathematics 2025-07-04 Sofwah Ahmad , Szymon Cygan , Grzegorz Karch

We discuss suitable classes of diffusion processes, for which functionals relevant to finance can be computed via Monte Carlo methods. In particular, we construct exact simulation schemes for processes from this class. However, should the…

Numerical Analysis · Mathematics 2012-04-06 Jan Baldeaux , Eckhard Platen

Structural causal models postulate noisy functional relations among a set of interacting variables. The causal structure underlying each such model is naturally represented by a directed graph whose edges indicate for each variable which…

Statistics Theory · Mathematics 2022-03-15 David Strieder , Tobias Freidling , Stefan Haffner , Mathias Drton

We derive an exact path integral formulation for the partition function for the Ising model using a mapping between spins and poles of a Laurent expansion for a field on the complex plane. The advantage in using this formulation for the…

Statistical Mechanics · Physics 2019-08-23 Francesco Caravelli

We propose an approach to compute the boundary crossing probabilities for a class of diffusion processes which can be expressed as piecewise monotone (not necessarily one-to-one) functionals of a standard Brownian motion. This class…

Probability · Mathematics 2007-05-23 Liqun Wang , Klaus Pötzelberger

The constructive martingale representation theorem of functional It\^o calculus is extended, from the space of square integrable martingales, to the space of local martingales. The setting is that of an augmented filtration generated by a…

Probability · Mathematics 2018-12-11 Kristoffer Lindensjö

We introduce a notion of nonlinear expectation --G--expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first discuss the notion of G-standard normal distribution. With this nonlinear distribution we can…

Probability · Mathematics 2007-05-23 Shige Peng

In this paper we examine a number of models that generate random fractals. The models are studied using the tools of computational complexity theory from the perspective of parallel computation. Diffusion limited aggregation and several…

Condensed Matter · Physics 2009-10-28 J. Machta , R. Greenlaw

In the present paper, we discuss solvability questions of a non-local problem with integral form transmitting conditions for diffusion-wave equation with the Caputo fractional derivative in a domain bounded by smooth curves. The uniqueness…

Analysis of PDEs · Mathematics 2015-07-07 P. Agarwal , A. S. Berdyshev , E. T. Karimov

This note is devoted to some nonlocal, nonlinear elliptic problems with an emphasis on the computation of the solution of such problems, reducing it in particular to a fixed point argument in R. Errors estimates and numerical experiments…

Analysis of PDEs · Mathematics 2026-01-28 M. M. Chipot , A. Luthra , S. A. Sauter

We present an ``equation-free'' multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast…

Numerical Analysis · Mathematics 2007-05-23 Dongbin Xiu , Ioannis Kevrekidis

For H\"older continuous functions $W(t,x)$ and $\varphi_t$, we define nonlinear integral $\int_a^b W(dt, \varphi_t)$ via fractional calculus. This nonlinear integral arises naturally in the Feynman-Kac formula for stochastic heat equations…

Probability · Mathematics 2021-10-12 Yaozhong Hu , Khoa Le

Denoising diffusion bridge models (DDBMs) are a powerful variant of diffusion models for interpolating between two arbitrary paired distributions given as endpoints. Despite their promising performance in tasks like image translation, DDBMs…

Machine Learning · Computer Science 2025-05-01 Kaiwen Zheng , Guande He , Jianfei Chen , Fan Bao , Jun Zhu

This tutorial provides a concise introduction to modern causal modeling by integrating potential outcomes and graphical methods. We motivate causal questions such as counterfactual reasoning under interventions and define binary treatments…

Methodology · Statistics 2025-06-27 Gauranga Kumar Baishya