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This paper considers the problem of designing time-dependent, real-time control policies for controllable nonlinear diffusion processes, with the goal of obtaining maximally-informative observations about parameters of interest. More…

Methodology · Statistics 2014-10-16 Giles Hooker , Kevin K. Lin , Bruce Rogers

We consider a decision maker who must choose an action in order to maximize a reward function that depends also on an unknown parameter {\Theta}. The decision maker can delay taking the action in order to experiment and gather additional…

Machine Learning · Statistics 2021-06-22 Victor F. Araman , Rene Caldentey

We develop a principled framework for analyzing and designing noise schedules in diffusion models. We show that one can recast this design problem as an optimal control problem, whose state is the Fisher information of the diffusion process…

Machine Learning · Computer Science 2026-05-22 Seo Taek Kong , Weina Wang , R. Srikant

We consider a simple mean reverting diffusion process, with piecewise constant drift and diffusion coefficients, discontinuous at a fixed threshold. We discuss estimation of drift and diffusion parameters from discrete observations of the…

Statistics Theory · Mathematics 2024-03-12 Sara Mazzonetto , Paolo Pigato

The analysis of diffusion processes in real-world propagation scenarios often involves estimating variables that are not directly observed. These hidden variables include parental relationships, the strengths of connections between nodes,…

Social and Information Networks · Computer Science 2016-05-12 Shohreh Shaghaghian , Mark Coates

In this article we consider the estimation of static parameters for partially observed diffusion processes with discrete-time observations over a fixed time interval. In particular, when one only has access to time-discretized solutions of…

Methodology · Statistics 2025-09-26 Miguel Alvarez , Ajay Jasra

In this paper we introduce a novel particle filter scheme for a class of partially-observed multivariate diffusions. %continuous-time dynamic models where the %signal is given by a multivariate diffusion process. We consider a variety of…

Methodology · Statistics 2007-10-24 Paul Fearnhead , Omiros Papaspiliopoulos , Gareth Roberts

We propose a new statistical observation scheme of diffusion processes named convolutional observation, where it is possible to deal with smoother observation than ordinary diffusion processes by considering convolution of diffusion…

Statistics Theory · Mathematics 2020-10-28 Shogo H Nakakita , Masayuki Uchida

We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion…

Biological Physics · Physics 2016-08-10 Christian L. Vestergaard

We study the Bayesian problems of detecting a change in the drift rate of an observable diffusion process with linear and exponential penalty costs for a detection delay. The optimal times of alarms are found as the first times at which the…

Statistics Theory · Mathematics 2011-11-08 Pavel V. Gapeev , Albert N. Shiryaev

Let $X_1,X_2,\ldots $ be independent random variables observed sequentially and such that $X_1,\ldots,X_{\theta-1}$ have a common probability density $p_0$, while $X_\theta,X_{\theta+1},\ldots $ are all distributed according to $p_1\neq…

Statistics Theory · Mathematics 2018-04-25 Yuri Golubev , Mher Safarian

Wet-lab experiments, in which the dynamics within living cells are observed, are usually costly and time consuming. This is particularly true if single-cell measurements are obtained using experimental techniques such as flow-cytometry or…

Cell Behavior · Quantitative Biology 2014-12-18 Charalampos Kyriakopoulos , Verena Wolf

To make decisions organisms often accumulate information across multiple timescales. However, most experimental and modeling studies of decision-making focus on sequences of independent trials. On the other hand, natural environments are…

Neurons and Cognition · Quantitative Biology 2018-06-12 Khanh P Nguyen , Kresimir Josic , Zachary P Kilpatrick

Modeling of longitudinal data often requires diffusion models that incorporate overall time-dependent, nonlinear dynamics of multiple components and provide sufficient flexibility for subject-specific modeling. This complexity challenges…

Methodology · Statistics 2017-01-31 Mareile Große Ruse , Adeline Samson , Susanne Ditlevsen

Diffusive transport is characterized by the scaling law $(length)^{2}\propto(time)$. In this letter we show that this relationship is significantly altered in curved analogue spacetimes. This circumstance provides an opportunity to tailor…

Statistical Mechanics · Physics 2012-06-21 Matteo Smerlak

Inference-time controllable generation is essential for real-world applications of unconditional diffusion models. However, most existing techniques focus on individual samples, struggling in applications that require the sample population…

Machine Learning · Computer Science 2026-05-11 Hao Luan , See-Kiong Ng , Chun Kai Ling

Of primary interest in this paper is the numerical approximation of a time dependent fractional, in space, diffusion equation where the domain is assumed to be nonhomogeneous, having different axial diffusion coefficients. This work is…

Numerical Analysis · Mathematics 2026-05-12 T. Catoe , V. J. Ervin

We provide a general method to analyze the asymptotic properties of a variety of estimators of continuous time diffusion processes when the data are not only discretely sampled in time but the time separating successive observations may…

Statistics Theory · Mathematics 2007-06-13 Yacine Ait-Sahalia , Per A. Mykland

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process which…

Computation · Statistics 2023-02-21 Ajay Jasra , Mohamed Maama , Hernando Ombao

For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical…

Applications · Statistics 2014-07-22 Xiao Lin , Gabriel Terejanu
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