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Efficiency of search for randomly distributed targets is a prominent problem in many branches of the sciences. For the stochastic process of L\'evy walks, a specific range of optimal efficiencies was suggested under variation of search…

Statistical Mechanics · Physics 2021-06-11 S. Mohsen J. Khadem , Sabine H. L. Klapp , Rainer Klages

We consider the problem of estimating parameter sensitivity for Markovian models of reaction networks. Sensitivity values measure the responsiveness of an output to the model parameters. They help in analyzing the network, understanding its…

Probability · Mathematics 2014-04-18 Ankit Gupta , Mustafa Khammash

Random walk centrality is a fundamental metric in graph mining for quantifying node importance and influence, defined as the weighted average of hitting times to a node from all other nodes. Despite its ability to capture rich graph…

Artificial Intelligence · Computer Science 2025-10-24 Changan Liu , Zixuan Xie , Ahad N. Zehmakan , Zhongzhi Zhang

Random walks are the simplest way to explore or search a graph, and have revealed a very useful tool to investigate and characterize the structural properties of complex networks from the real world, e.g. they have been used to identify the…

Statistical Mechanics · Physics 2020-06-11 Timoteo Carletti , Malbor Asllani , Duccio Fanelli , Vito Latora

In this work we derandomize two central results in graph algorithms, replacement paths and distance sensitivity oracles (DSOs) matching in both cases the running time of the randomized algorithms. For the replacement paths problem, let G =…

Data Structures and Algorithms · Computer Science 2019-05-21 Noga Alon , Shiri Chechik , Sarel Cohen

In this paper, we develop a class of robust numerical methods for solving dynamical systems with multiple time scales. We first represent the solution of a multiscale dynamical system as a transformation of a slowly varying solution. Then,…

Numerical Analysis · Mathematics 2019-09-11 Thomas Y. Hou , Zhongjian Wang , Zhiwen Zhang

We present an efficient finite difference method for the computation of parameter sensitivities that is applicable to a wide class of continuous time Markov chain models. The estimator for the method is constructed by coupling the perturbed…

Numerical Analysis · Mathematics 2012-05-14 David F. Anderson

We present an algorithm for marginalising changepoints in time-series models that assume a fixed number of unknown changepoints. Our algorithm is differentiable with respect to its inputs, which are the values of latent random variables…

Machine Learning · Computer Science 2019-11-25 Hyoungjin Lim , Gwonsoo Che , Wonyeol Lee , Hongseok Yang

This paper develops a framework for the error analysis in nonparametric model fitting of fractional stochastic differential equations based on discrete observations. We identify and quantify the main error sources -- time discretization,…

Probability · Mathematics 2026-05-07 Mahdi Dehshiri , Kerlyns Martinez , Lauri Viitasaari

Our study focuses on fractional order compartment models derived from underlying physical stochastic processes, providing a more physically grounded approach compared to models that use the dynamical system approach by simply replacing…

This article introduces a framework for measuring the uncertain behaviour of a changing system in terms of the solution of a class of fractional stochastic differential equations (fsDEs). This is accomplished via operational matrices based…

General Mathematics · Mathematics 2025-06-03 O. T. Birgani , J. F. Peters , S. Kouhkani

Exponential time differencing methods is a power tool for high-performance numerical simulation of computationally challenging problems in condensed matter physics, fluid dynamics, chemical and biological physics, where mathematical models…

Numerical Analysis · Mathematics 2024-10-15 Evelina V. Permyakova , Denis S. Goldobin

We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so far has been to use a factorised posterior distribution,…

Machine Learning · Statistics 2018-12-17 Alessandro Davide Ialongo , Mark van der Wilk , James Hensman , Carl Edward Rasmussen

Researchers have designed many algorithms to measure the distances between graph nodes, such as average hitting times of random walks, cosine distances from DeepWalk, personalized PageRank, etc. Successful although these algorithms are,…

Discrete Mathematics · Computer Science 2020-12-02 Enzhi Li , Zhengyi Le

Random walks find applications in many areas of science and are the heart of essential network analytic tools. When defined on temporal networks, even basic random walk models may exhibit a rich spectrum of behaviours, due to the…

Physics and Society · Physics 2019-11-11 Julien Petit , Renaud Lambiotte , Timoteo Carletti

This paper provides an analytical methodology to compute the sensitivities with respect to system parameters for any second order hybrid Ordinary Differential Equation (ODE) system. The hybrid ODE system is characterized by discontinuities…

Optimization and Control · Mathematics 2017-10-13 Sebastien Corner , Corina Sandu , Adrian Sandu

We propose a method for zeroth order stochastic convex optimization that attains the suboptimality rate of $\tilde{\mathcal{O}}(n^{7}T^{-1/2})$ after $T$ queries for a convex bounded function $f:{\mathbb R}^n\to{\mathbb R}$. The method is…

Machine Learning · Computer Science 2014-02-13 Tengyuan Liang , Hariharan Narayanan , Alexander Rakhlin

An exact discretization method is being developed for solving linear systems of ordinary fractional-derivative differential equations with constant matrix coefficients (LSOFDDECMC). It is shown that the obtained linear discrete system in…

Dynamical Systems · Mathematics 2019-03-18 Fikret A. Aliev , N. A. Aliev , N. I. Velieva , K. G. Gasimova , Y. V Mamedova

It has been recognized that using time-varying initialization functions to solve the initial value problem of fractional-order systems (FOS) is both complex and essential in defining the dynamical behavior of the states of FOSs. In this…

Methodology · Statistics 2022-10-19 Mohamed A. Bahloul , Zehor Belkhatir , Taous-Meriem laleg-Kirati

In complex physical systems, conventional differential equations often fall short in capturing non-local and memory effects, as they are limited to local dynamics and integer-order interactions. This study introduces a stepwise data-driven…

Computational Physics · Physics 2025-05-30 Xiangnan Yu , Hao Xu , Zhiping Mao , HongGuang Sun , Yong Zhang , Dongxiao Zhang , Yuntian Chen