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The Geometrically Intrinsic Nonlinear Recursive Filter, or GI Filter, is designed to estimate an arbitrary continuous-time Markov diffusion process X subject to nonlinear discrete-time observations. The GI Filter is fundamentally different…

Optimization and Control · Mathematics 2007-05-23 R. W. R. Darling

This paper contains the technical foundations from stochastic differential geometry for the construction of geometrically intrinsic nonlinear recursive filters. A diffusion X on a manifold N is run for a time interval T, with a random…

Probability · Mathematics 2007-05-23 R. W. R. Darling

Intrinsic location functional is a large class of random locations containing locations that one may encounter in many cases, e.g., the location of the path supremum/infimum over a given interval, the first/last hitting time, etc. It has…

Probability · Mathematics 2014-12-09 Yi Shen

This paper proposes a probabilistic approach to the problem of intrinsic filtering of a system on a matrix Lie group with invariance properties. The problem of an invariant continuous-time model with discrete-time measurements is cast into…

Systems and Control · Computer Science 2016-02-22 Axel Barrau , Silvere Bonnabel

We construct intrinsic on-and off-diagonal upper and lower estimates for the transition probability density of a L\'evy process in small time. By intrinsic we mean that such estimates reflect the structure of the characteristic exponent of…

Probability · Mathematics 2013-08-09 Victoria Knopova , Alexei Kulik

In statistics on manifolds, the notion of the mean of a probability distribution becomes more involved than in a linear space. Several location statistics have been proposed, which reduce to the ordinary mean in Euclidean space. A…

Statistics Theory · Mathematics 2024-11-05 Till Düsberg , Benjamin Eltzner

A basic problem in machine learning is to find a mapping $f$ from a low dimensional latent space $\mathcal{Y}$ to a high dimensional observation space $\mathcal{X}$. Modern tools such as deep neural networks are capable to represent general…

Machine Learning · Computer Science 2022-08-02 Ke Sun

Identifying an appropriate covariance function is one of the primary interests in spatial and spatio-temporal statistics because it allows researchers to analyze the dependence structure of the random process. For this purpose, spatial…

Methodology · Statistics 2025-02-04 Jongwook Kim , Chunfeng Huang , Nicholas Bussberg

We consider large deviations of empirical measures of diffusion processes. In a first part, we present conditions to obtain a large deviations principle (LDP) for a precise class of unbounded functions. This provides an analogue to the…

Probability · Mathematics 2020-09-23 Grégoire Ferré , Gabriel Stoltz

This paper considers reparameterization invariant Bayesian point estimates and credible regions of model parameters for scientific inference and communication. The effect of intrinsic loss function choice in Bayesian intrinsic estimates and…

Methodology · Statistics 2021-09-23 Aki Vehtari

Sampling viable 3D structures (e.g., molecules and point clouds) with SE(3)-invariance using diffusion-based models proved promising in a variety of real-world applications, wherein SE(3)-invariant properties can be naturally characterized…

Machine Learning · Computer Science 2024-03-05 Zihan Zhou , Ruiying Liu , Jiachen Zheng , Xiaoxue Wang , Tianshu Yu

Recently, the intrinsic sampling method has been developed in order to obtain, from molecular simulations, the intrinsic structure of the liquid-vapor interface that is presupposed in the classical capillary wave theory. Our purpose here is…

Soft Condensed Matter · Physics 2009-11-13 Daniel Duque , Pedro Tarazona , Enrique Chacón

We consider iterated function systems on the interval with random perturbation. Let $Y_\epsilon$ be uniformly distributed in $[1- \epsilon, 1 + \epsilon]$ and let $f_i \in C^{1+\alpha}$ be contractions with fixpoints $a_i$. We consider the…

Dynamical Systems · Mathematics 2015-08-25 Balazs Barany , Tomas Persson

This work aims at making a comprehensive contribution in the general area of parametric inference for discretely observed diffusion processes. Established approaches for likelihood-based estimation invoke a time-discretisation scheme for…

Methodology · Statistics 2024-01-30 Yuga Iguchi , Alexandros Beskos , Matthew M. Graham

The aim of this paper is two-fold: First, we obtain a better understanding of the intrinsic distance of diffusion processes. Precisely, (i) for all $n\ge1$, the diffusion matrix $A$ is weak upper semicontinuous on $\Omega$ if and only if…

Classical Analysis and ODEs · Mathematics 2013-05-28 Pekka Koskela , Nageswari Shanmugalingam , Yuan Zhou

We consider diffusion of independent molecules in an insulated Euclidean domain with unknown diffusivity parameter. At a random time and position, the molecules may bind and stop diffusing in dependence of a given `binding potential'. The…

Statistics Theory · Mathematics 2026-03-18 Richard Nickl , Fanny Seizilles

The effect of the correlations in the diluteness pattern in the systems with non-integral dimensionality, on $\nu=\frac{4}{5}$ superdiffusion process is considered in this paper. These spatial correlations have proved to be very effective…

Statistical Mechanics · Physics 2019-09-04 J. Cheraghalizadeh , M. N. Najafi

The bacteria metabolic process of open nonlinear dissipative system far from equilibrium point is modeled using classical methods of synergetics. The invariant measure and its convergence in the phase space of the system was obtained in…

Chaotic Dynamics · Physics 2025-04-16 V. Grytsay

In this paper we prove the Local Asymptotic Mixed Normality (LAMN) property for the statistical model given by the observation of local means of a diffusion process $X$. Our data are given by $ \int_0^1 X_{\frac{s+i}{n}} \dd \mu (s)$ for…

Probability · Mathematics 2009-06-09 Arnaud Gloter , Emmanuel Gobet

We consider a family of random locations, called intrinsic location functionals, of periodic stationary processes. This family includes but is not limited to the location of the path supremum and first/last hitting times. We first show that…

Probability · Mathematics 2018-04-06 Jie Shen , Yi Shen , Ruodu Wang
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