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We study classical stochastic systems with discrete states, coupled to switching external environments. For fast environmental processes we derive reduced dynamics for the system itself, focusing on corrections to the adiabatic limit of…

Statistical Mechanics · Physics 2019-03-27 Peter G. Hufton , Yen Ting Lin , Tobias Galla

In this paper, we apply a recently developed nonparametric modeling approach, the "diffusion forecast", to predict the time-evolution of Fourier modes of turbulent dynamical systems. While the diffusion forecasting method assumes the…

Chaotic Dynamics · Physics 2016-03-23 Tyrus Berry , John Harlim

Delays in biological systems may be used to model events for which the underlying dynamics cannot be precisely observed. Mathematical modeling of biological systems with delays is usually based on Delay Differential Equations (DDEs), a kind…

Quantitative Methods · Quantitative Biology 2009-10-08 Roberto Barbuti , Giulio Caravagna , Paolo Milazzo , Andrea Maggiolo-Schettini

An essential input of annuity pricing is the future retiree mortality. From observed age-specific mortality data, modeling and forecasting can be taken place in two routes. On the one hand, we can first truncate the available data to…

Applications · Statistics 2020-09-21 Han Lin Shang , Steven Haberman

Real-world data often exhibits sequential dependence, across diverse domains such as human behavior, medicine, finance, and climate modeling. Probabilistic methods capture the inherent uncertainty associated with prediction in these…

Machine Learning · Statistics 2024-03-08 Alex Boyd

The proposed stochastic model for pedestrian dynamics is based on existing approaches using cellular automata, combined with substantial extensions, to compensate the deficiencies resulting of the discrete grid structure. This agent motion…

Physics and Society · Physics 2021-04-01 Michael Schultz

The imputation of missing values represents a significant obstacle for many real-world data analysis pipelines. Here, we focus on time series data and put forward SSSD, an imputation model that relies on two emerging technologies,…

Machine Learning · Computer Science 2023-05-09 Juan Miguel Lopez Alcaraz , Nils Strodthoff

The paper introduces a novel topological method for prediction and modeling for a nonlinear time--series that exhibit recurring patterns. According to the model, global manifold of the reconstructed state--space can be approximated by a few…

Chaotic Dynamics · Physics 2017-11-21 Sajini Anand P S , Prabhakar G Vaidya

In this work, we propose an approach to generalize denoising diffusion probabilistic models for stock market predictions and portfolio management. Present works have demonstrated the efficacy of modeling interstock relations for market…

Machine Learning · Computer Science 2024-03-22 Divyanshu Daiya , Monika Yadav , Harshit Singh Rao

The current survey paper concerns stochastic mathematical models for the spread of infectious diseases. It starts with the simplest setting of a homogeneous population in which a transmittable disease spreads during a short outbreak.…

Applications · Statistics 2018-01-30 Tom Britton

This article analyzes the problem of estimating the time until an event occurs, also known as survival modeling. We observe through substantial experiments on large real-world datasets and use-cases that populations are largely…

Machine Learning · Computer Science 2019-05-13 David Hubbard , Benoit Rostykus , Yves Raimond , Tony Jebara

A calculational approach in fluid turbulence is presented. Use is made of the attracting nature of the fluid-dynamic dynamical system. An approximate approach is offerred that effectively propagates the statistics in time. Loss of…

Fluid Dynamics · Physics 2007-05-23 Edsel A. Ammons

This paper presents a novel approach to stochastic mortality modelling by using the Conway--Maxwell--Poisson (CMP) distribution to model death counts. Unlike standard Poisson or negative binomial distributions, the CMP is a more adaptable…

Methodology · Statistics 2026-01-06 Jackie Siaw Tze Wong , Emiliano A. Valdez

In the domains of image and audio, diffusion models have shown impressive performance. However, their application to discrete data types, such as language, has often been suboptimal compared to autoregressive generative models. This paper…

Machine Learning · Computer Science 2024-05-29 Severi Rissanen , Markus Heinonen , Arno Solin

In this work, we consider systems that are subjected to intermittent instabilities due to external stochastic excitation. These intermittent instabilities, though rare, have a large impact on the probabilistic response of the system and…

Chaotic Dynamics · Physics 2017-06-02 Mustafa A. Mohamad , Themistoklis P. Sapsis

Diffusion models have demonstrated significant potential in achieving state-of-the-art performance across various text generation tasks. In this systematic study, we investigate their application to the table-to-text problem by adapting the…

Computation and Language · Computer Science 2024-09-24 Aleksei S. Krylov , Oleg D. Somov

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

Recently, we have shown that the age-specific prevalence of a disease can be related to the transition rates in the illness-death model via a partial differential equation (PDE). In case of a chronic disease, we show that the PDE can be…

Populations and Evolution · Quantitative Biology 2017-12-29 Ralph Brinks

A recent report from the World Meteorological Organization (WMO) highlights that water-related disasters have caused the highest human losses among natural disasters over the past 50 years, with over 91\% of deaths occurring in low-income…

Machine Learning · Computer Science 2025-01-14 Ting-Yu Dai , Hayato Ushijima-Mwesigwa

The mean residual life function is a key functional for a survival distribution. It has a practically useful interpretation as the expected remaining lifetime given survival up to a particular time point, and it also characterizes the…

Applications · Statistics 2024-01-26 Valerie Poynor , Athanasios Kottas