From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation by Seok Joo Chae, Seolah Shin, Kangmin Lee, Seunggyu Lee, Jae Kyoung Kim

“…While both the stochastic total quasi-steady state approximation (stQSSA) and the stochastic low-state quasi-steady-state approximation (slQSSA) reduced simulation time, only the slQSSA provided an accurate model reduction. …”
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Representation of Manifolds for the Stochastic Swift-Hohenberg Equation with Multiplicative Noise by Yanfeng Guo, Donglong Li

“…Representation of approximation for manifolds of the stochastic Swift-Hohenberg equation with multiplicative noise has been investigated via non-Markovian reduced system. …”
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An Improved Stochastic Configuration Networks With Compact Structure and Parameter Adaptation by Sanyi Li, Hongyu Guan, Peng Liu, Weichao Yue, Qian Wang

“…Stochastic Configuration Networks (SCNs) perform well in machine learning and data mining tasks in complex data environments. …”
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Implicit Numerical Solutions for Solving Stochastic Differential Equations with Jumps by Ying Du, Changlin Mei

“…Considering the fact that the use of the explicit methods often results in instability and inaccurate approximations in solving stochastic differential equations, we propose two implicit methods, the θ-Taylor method and the balanced θ-Taylor method, for numerically solving the stochastic differential equation with jumps and prove that the numerical solutions are convergent with strong order 1.0. …”
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Calibration verification for stochastic agent-based disease spread models. by Maya Horii, Aidan Gould, Zachary Yun, Jaideep Ray, Cosmin Safta, Tarek Zohdi

“…In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. …”
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Approximation of a positive random variable distribution by the mixture of exponential distsibutions by Eimutis Valakevičius

“… In the paper is proposed a method how to approximate the model of non-markovian stochastic system by markovian one with a countable space of states and continuous time. …”
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Generalized Synchronization of Stochastic Discrete Chaotic System with Poisson Distribution Coefficient by Shao-juan Ma, Duan Dong, Jie Zheng

“…This paper addresses the generalized synchronization of stochastic discrete chaotic systems with Poisson distribution coefficient. …”
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Orchard: Building large cancer phylogenies using stochastic combinatorial search. by Ethan Kulman, Rui Kuang, Quaid Morris

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Spatio-temporal modelling of extreme low birth rates in U.S. counties by Kai Wang, Yingqing Zhang, Long Bai, Ying Chen, Chengxiu Ling

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Testing Data Cloning as the Basis of an Estimator for the Stochastic Volatility in Mean Model by E. Romero, E. Ropero-Moriones

“…Developed as a refinement of stochastic volatility (SV) models, the stochastic volatility in mean (SVM) model incorporates the latent volatility as an explanatory variable in both the mean and variance equations. …”
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Anomaly detection model for multivariate time series based on stochastic Transformer by Weigang HUO, Rui LIANG, Yonghua LI

“…Aiming at the problem that the existing multivariate time series anomaly detection models based on variational autoencoders could not propagate long-term temporal dependencies between stochastic variables in latent space, the stochastic Transformer for MTS anomaly detection (ST-MTS-AD) model which combined Transformer encoder with VAE was proposed.In the inference network of the ST-MTS-AD, the MTS long-term temporal dependent features generated by Transformer encoder and the sampled values of the stochastic variables at the previous moment were inputted into the multilayer perceptron, the approximate posterior distribution of the stochastic variables at the current moment was generated by the multilayer perceptron, and the temporal dependencies between stochastic variables were realized.The gated transition function(GTF) was used to generate the prior distribution of stochastic variables.The generation network of the ST-MTS-AD reconstructed the distribution of the MTS values at each moment by the multilayer perceptron whose input was the MTS long-term temporal dependent features generated by the inference network and the approximate posterior sampling values of stochastic variables.The distribution of normal MTS dataset was learned by the variational inference technology, and the abnormal MTS segment was determined by the log-likelihood of the reconstruction probability.Experiments on four public datasets show that the ST-MTS-AD model significantly improves the F1 score over the typical baseline models.…”
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An Averaging Principle for Stochastic Differential Delay Equations with Fractional Brownian Motion by Yong Xu, Bin Pei, Yongge Li

“…An averaging principle for a class of stochastic differential delay equations (SDDEs) driven by fractional Brownian motion (fBm) with Hurst parameter in (1/2,1) is considered, where stochastic integration is convolved as the path integrals. …”
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Pricing Arithmetic Asian Options under Hybrid Stochastic and Local Volatility by Min-Ku Lee, Jeong-Hoon Kim, Kyu-Hwan Jang

“…Recently, hybrid stochastic and local volatility models have become an industry standard for the pricing of derivatives and other problems in finance. …”
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Stability and Complexity Analysis of Temperature Index Model Considering Stochastic Perturbation by Jing Wang

“…A temperature index model with delay and stochastic perturbation is constructed in this paper. …”
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Derivation and computation of discrete-delayand continuous-delay SDEs in mathematical biology by Edward J. Allen

“…Stochastic versions of several discrete-delay and continuous-delay differential equations, useful in mathematical biology, are derived from basic principles carefully taking into account the demographic, environmental, or physiological randomness in the dynamic processes. …”
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Comparing an Approximate Queuing Approach with Simulation for the Solution of a Cross-Docking Problem by Roberta Briesemeister, Antônio G. N. Novaes

“…It is observed that the stochastic queuing process may not reach the steady equilibrium state. …”
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Fractional Brownian Motion for a System of Fuzzy Fractional Stochastic Differential Equation by Kinda Abuasbeh, Ramsha Shafqat

“…Under various assumptions regarding the coefficients, we investigate the existence-uniqueness of the solution using an approximation method to the fractional stochastic integral. …”
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Expected Residual Minimization Method for a Class of Stochastic Quasivariational Inequality Problems by Hui-Qiang Ma, Nan-Jing Huang

“…We consider the expected residual minimization method for a class of stochastic quasivariational inequality problems (SQVIP). …”
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Minimum-cost network hardening algorithm based on stochastic loose optimize strategy by Guang-sheng ZHAO, Qing-feng CHENG, Yong-lin SUN

“…To construst a minimum-cost network hardening (MCNH) scheme in large-scale network,a stochastic loose optimize strategy based algorithm (MCNHA-SLOS) was proposed,and its effectiveness was analyzed.MCNHA-SLOS was a near-optimal approximation algorithm,which could achieve iterative computations in the array of sparse spaces of the whole plan space,so that the near-optimal scheme must exist in the low cost plan space.Instantiation analysis and experimental results show that the MCNHA-SLOS algorithm to be efficient,precision controllable and asymptotically optimal,and thus very applicable for large-scale network.…”
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Hopf Bifurcations of a Stochastic Fractional-Order Van der Pol System by Xiaojun Liu, Ling Hong, Lixin Yang

“…Firstly, the Chebyshev polynomial approximation is applied to study the stochastic fractional-order system. …”
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