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Related papers: On hypoellipticity of degenerate operators in test…

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We analyze quantal Brownian motion in $d$ dimensions using the unified model for diffusion localization and dissipation, and Feynman-Vernon formalism. At high temperatures the propagator possess a Markovian property and we can write down an…

Condensed Matter · Physics 2009-10-31 Doron Cohen

We study parametric inference for ergodic diffusion processes with a degenerate diffusion matrix. Existing research focuses on a particular class of hypo-elliptic SDEs, with components split into `rough'/`smooth' and noise from rough…

Statistics Theory · Mathematics 2024-05-29 Yuga Iguchi , Alexandros Beskos , Matthew Graham

This work presents a tensorial approach to constructing data-driven reduced-order models corresponding to semi-discrete partial differential equations with canonical Hamiltonian structure. By expressing parameter-varying operators with…

Numerical Analysis · Mathematics 2025-05-14 Arjun Vijaywargiya , Shane A. McQuarrie , Anthony Gruber

We study the overdetermined problem for a large family of non-local operators given by generators of subordinate Brownian motions. In particular, this family includes the fractional Laplacian, relativistic stable operators etc. We consider…

Analysis of PDEs · Mathematics 2025-06-23 Anup Biswas , Sven Jarohs

The F\"ollmer process is a Brownian motion conditioned to have a pre-specified distribution at time 1. This process can be interpreted as an "augmented" time-compressed version of the reverse stochastic differential equation (SDE) for the…

Machine Learning · Statistics 2026-05-19 Yuta Koike

We study the long time behaviour of a large class of diffusion processes on $R^N$, generated by second order differential operators of (possibly) degenerate type. The operators that we consider {\em need not} satisfy the H\"ormander…

Probability · Mathematics 2019-06-04 T. Cass , D. Crisan , P. Dobson , M. Ottobre

In this paper, we consider an expanding construction of a distributed control system, which is obtained by adding a new subsystem one after the other, until all $n$ subsystems, where $n \ge 2$, are included in the distributed control…

Optimization and Control · Mathematics 2014-09-30 Getachew K. Befekadu , Panos J. Antsaklis

In this paper we consider the wave equations for hypoelliptic homogeneous left-invariant operators on graded Lie groups with time-dependent H\"older propagation speeds. The examples are the time-dependent wave equation for the sub-Laplacian…

Analysis of PDEs · Mathematics 2017-08-01 Michael Ruzhansky , Chiara-Alba Taranto

This paper extends a class of degenerate elliptic operators for which hypoellipticity requires more than a logarithmic gain of derivatives of a solution in every direction. Work of Hoshiro and Morimoto in late 80s characterized a necessity…

Analysis of PDEs · Mathematics 2023-09-06 Timur Akhunov , Lyudmila Korobenko

This work extends the applications of Anderson-type Hamiltonians to include transport characterized by anomalous diffusion. Herein, we investigate the transport properties of a one-dimensional disordered system that employs the discrete…

Mathematical Physics · Physics 2020-03-06 J. L. Padgett , E. G. Kostadinova , C. D. Liaw , K. Busse , L. S. Matthews , T. W. Hyde

Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenarios where training samples are readily available, which is not…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Ayush Tewari , Tianwei Yin , George Cazenavette , Semon Rezchikov , Joshua B. Tenenbaum , Frédo Durand , William T. Freeman , Vincent Sitzmann

The extraction of nonstationary signals from blind and semi-blind multivariate observations is a recurrent problem. Numerous algorithms have been developed for this problem, which are based on the exact or approximate joint diagonalization…

Signal Processing · Electrical Eng. & Systems 2021-08-27 Reza Sameni , Christian Jutten

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian…

Numerical Analysis · Mathematics 2023-01-18 Mengwu Guo , Shane A. McQuarrie , Karen E. Willcox

We demonstrate that stochastic differential equations (SDEs) driven by fractional Brownian motion with Hurst parameter H > 1/2 have similar ergodic properties as SDEs driven by standard Brownian motion. The focus in this article is on…

Probability · Mathematics 2010-05-14 Martin Hairer , Natesh S. Pillai

A core challenge in Machine Learning is to learn to disentangle natural factors of variation in data (e.g. object shape vs. pose). A popular approach to disentanglement consists in learning to map each of these factors to distinct subspaces…

Machine Learning · Computer Science 2021-02-11 Diane Bouchacourt , Mark Ibrahim , Stéphane Deny

This article studies the global hypoellipticity of a class of overdetermined systems of pseudo-differential operators defined on the torus. The main goal consists in establishing connections between the global hypoellipticity of the system…

Analysis of PDEs · Mathematics 2020-07-16 Cleber de Medeira , Fernando de Avila Silva

Weak variance generalised gamma convolution processes are multivariate Brownian motions weakly subordinated by multivariate Thorin subordinators. Within this class, we extend a result from strong to weak subordination that a driftless…

Probability · Mathematics 2019-03-05 Boris Buchmann , Kevin W. Lu , Dilip B. Madan

Nonlinear systems, such as with degrading hysteretic behavior, are often encountered in engineering applications. In addition, due to the ubiquitous presence of uncertainty and the modeling of such systems becomes increasingly difficult. On…

Machine Learning · Statistics 2023-04-26 Subhayan De , Patrick T. Brewick

In this paper, we study a class of convolution operators on the space of distributions that enlarge the well-studied class of passive operators. In this larger class, we are able to associate, to each operator, a holomorphic function in the…

Functional Analysis · Mathematics 2018-11-27 Mitja Nedic

We study an abstract family of asymptotically degenerating variational problems. Those are natural generalisations of families of problems emerging upon application of a rescaled Floquet-Bloch-Gelfand transform to resolvent problems for…

Analysis of PDEs · Mathematics 2025-08-27 Shane Cooper , Ilia Kamotski , Valery P. Smyshlyaev