Výsledky vyhledávání - "Numerical analysis or methods applied to Markov chains"

Solving Stationary Nonlinear Fokker–Planck Equations via Sampling: Solving stationary nonlinear Fokker-Planck equations via sampling

Autoři: Lei Li Yijia Tang Jingtong Zhang

Zdroj: SIAM Journal on Applied Mathematics. 85:249-277

Témata: ddc:004, McKean-Vlasov equation, Gibbs distribution, 65C05, 65C40, 65N75, DATA processing & computer science, Monte Carlo methods, Numerical Analysis (math.NA), mean-field limit, random batch Monte Carlo method, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2310.00544

A note on numerical methods for mean-variance portfolio selection with dynamic attention behavior in a hidden Markov model

Autoři: Zhang, Yu Jin, Zhuo Wei, Jiaqin

Zdroj: Numerical Algebra, Control and Optimization. 15:77-107

Témata: mean-variance, Portfolio theory, Markov chain approximation, deep learning, Numerical analysis or methods applied to Markov chains, dynamic attention behavior, hidden Markov model, extended HJB equation, Artificial neural networks and deep learning

Popis souboru: application/xml

Přístupová URL adresa: https://zbmath.org/7985286
https://doi.org/10.3934/naco.2024034

A Numerical Truncation Approximation with A Posteriori Error Bounds for the Solution of Poisson’s Equation: A numerical truncation approximation with a posteriori error bounds for the solution of Poisson's equation

Autoři: Mahdian, Saied Glynn, Peter W. Liu, Yuanyuan

Zdroj: Methodology and Computing in Applied Probability. 27

Témata: Jump processes on discrete state spaces, Computational methods in Markov chains, Markov chain, state space truncation, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis, numerical bounds, Poisson equation, Markov jump process, Markov chains (discrete-time Markov processes on discrete state spaces), Mathematics - Probability, Continuous-time Markov processes on discrete state spaces, Lyapunov functions

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2401.15905

Transient Subtraction: A Control Variate Method for Computing Transport Coefficients: Transient subtraction: a control variate method for computing transport coefficients

Autoři: Spacek, Renato Monmarché, Pierre Stoltz, Gabriel

Přispěvatelé: Spacek, Renato Monmarché, Pierre Stoltz, Gabriel

Zdroj: Journal of Statistical Physics

Témata: [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Statistical Mechanics (cond-mat.stat-mech), variance reduction, FOS: Physical sciences, Numerical Analysis (math.NA), [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], Applications of functional analysis in probability theory and statistics, Langevin dynamics, stochastic differential equations, [PHYS.COND.CM-SM] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], 82C31, 65C40, 46N30, Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics, transport coefficients, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis, Condensed Matter - Statistical Mechanics

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2410.00212
https://zbmath.org/8032091
https://doi.org/10.1007/s10955-025-03424-x

Residual multi-fidelity neural network computing

Autoři: Owen Davis Mohammad Motamed Raúl Tempone

Zdroj: BIT Numerical Mathematics. 65

Témata: Numerical solutions to stochastic differential and integral equations, FOS: Computer and information sciences, Computer Science - Machine Learning, uncertainty quantification, 65C30, 65C40, 68T07, Numerical Analysis (math.NA), multi-fidelity computing, Machine Learning (cs.LG), deep neural networks, FOS: Mathematics, residual modeling, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis, Artificial neural networks and deep learning

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2310.03572
https://zbmath.org/8012154
https://doi.org/10.1007/s10543-025-01058-9

Modified Riccati iterative algorithms for stochastic coupled algebraic Riccati equations of linear stochastic Markovian jump systems

Autoři: Meijun Liu Xueyan Zhao Feiqi Deng

Zdroj: Asian Journal of Control. 26:1787-1796

Témata: 0209 industrial biotechnology, Linear-quadratic optimal control problems, 0202 electrical engineering, electronic engineering, information engineering, stochastic coupled algebraic Riccati equations (SCAREs), Numerical analysis or methods applied to Markov chains, Optimality conditions for problems involving randomness, 02 engineering and technology, Stochastic stability in control theory, Feedback control, linear stochastic Markovian jump systems, Riccati iterative algorithms

Popis souboru: application/xml

Přístupová URL adresa: https://zbmath.org/7964801
https://doi.org/10.1002/asjc.3300

An ergodic theorem for the weighted ensemble method

Autoři: Aristoff, David

Zdroj: Journal of Applied Probability. 59:152-166

Témata: Probability (math.PR), Stochastic particle methods, FOS: Physical sciences, Monte Carlo methods, Numerical Analysis (math.NA), Mathematical Physics (math-ph), sequential Monte Carlo, weighted ensemble, 01 natural sciences, importance sampling, stratification, 65C05, 65C35, 65C40, 0103 physical sciences, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, steady state, Mathematics - Numerical Analysis, 0101 mathematics, interacting particle system, Mathematical Physics, Mathematics - Probability, ergodic theorem

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/pdf/1906.00856
http://arxiv.org/abs/1906.00856
https://zbmath.org/7501655
https://doi.org/10.1017/jpr.2021.38

On the accept–reject mechanism for Metropolis–Hastings algorithms: On the accept-reject mechanism for Metropolis-Hastings algorithms

Autoři: Glatt-Holtz, Nathan Krometis, Justin Mondaini, Cecilia

Zdroj: The Annals of Applied Probability. 33

Témata: FOS: Computer and information sciences, Probability (math.PR), 65P10, 65C05, Markov chain Monte Carlo (MCMC) algorithms, Monte Carlo methods, Mathematics - Statistics Theory, Metropolis-Hastings algorithms, sampling on abstract state spaces, Statistics Theory (math.ST), Numerical Analysis (math.NA), surrogate trajectory methods, 01 natural sciences, Methodology (stat.ME), Computational methods in Markov chains, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, Hamiltonian Monte Carlo, Mathematics - Numerical Analysis, 0101 mathematics, Mathematics - Probability, Statistics - Methodology

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2011.04493
https://zbmath.org/7791536
https://doi.org/10.1214/23-aap1948

Mixing rates for Hamiltonian Monte Carlo algorithms in finite and infinite dimensions

Autoři: Nathan E. Glatt-Holtz Cecilia F. Mondaini

Zdroj: Stochastics and Partial Differential Equations: Analysis and Computations. 10:1318-1391

Témata: FOS: Computer and information sciences, 62C10, 11K45, 37K99, Probability (math.PR), infinite-dimensional Hamiltonian systems, Monte Carlo methods, Mathematics - Statistics Theory, Bayesian inversion, Statistics Theory (math.ST), advection-diffusion equations, Hamiltonian Monte Carlo (HMC), Statistics - Computation, 01 natural sciences, Mathematics - Analysis of PDEs, Stochastic partial differential equations (aspects of stochastic analysis), passive scalar transport, Computational methods in Markov chains, Markov chain Monte Carlo (MCMC), FOS: Mathematics, Numerical analysis or methods applied to Markov chains, 0101 mathematics, statistical sampling, Mathematics - Probability, Computation (stat.CO), Analysis of PDEs (math.AP)

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/pdf/2003.07980
http://arxiv.org/abs/2003.07980
https://link.springer.com/article/10.1007/s40072-021-00211-z

Conditional sequential Monte Carlo in high dimensions

Autoři: Finke, Axel Thiery, Alexandre H.

Zdroj: The Annals of Statistics. 51

Témata: particle filter, FOS: Computer and information sciences, state-space model, Stochastic particle methods, Monte Carlo methods, curse of dimension, Statistics - Computation, 01 natural sciences, Markov chain Monte Carlo, Discrete-time Markov processes on general state spaces, high dimensions, Numerical analysis or methods applied to Markov chains, 0101 mathematics, Computation (stat.CO)

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2108.10277

Optimizing Weighted Ensemble Sampling of Steady States: Optimizing weighted ensemble sampling of steady states

Autoři: David Aristoff Daniel M. Zuckerman

Zdroj: Multiscale Modeling & Simulation. 18:646-673

Témata: Markov chains, reaction networks, Monte Carlo methods, Parallel numerical computation, Numerical Analysis (math.NA), sequential Monte Carlo, weighted ensemble, 01 natural sciences, molecular dynamics, Probabilistic models, generic numerical methods in probability and statistics, 0104 chemical sciences, resampling, coarse graining, 0103 physical sciences, FOS: Mathematics, Numerical methods of time-dependent statistical mechanics, Numerical analysis or methods applied to Markov chains, steady state, Mathematics - Numerical Analysis, 65C05, 65C20, 65C40, 65Y05, 82C80

Popis souboru: application/xml

Přístupová URL adresa: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378190
https://pubmed.ncbi.nlm.nih.gov/34421402
http://arxiv.org/abs/1806.00860
https://zbmath.org/7205781
https://doi.org/10.1137/18m1212100
https://ohsu.pure.elsevier.com/en/publications/optimizing-weighted-ensemble-sampling-of-steady-states
https://europepmc.org/article/PMC/PMC8378190
https://www.ncbi.nlm.nih.gov/pubmed/34421402
https://doi.org/10.1137/18M1212100
https://dl.acm.org/doi/10.1137/18M1212100
https://epubs.siam.org/doi/10.1137/18M1212100

Asynchronous finite-time extended dissipative filter on linear neutral semi-Markov jump systems under sensor saturation and dual-channel DoS attacks

Autoři: Guifang Cheng Hao Liu

Zdroj: Applied Mathematics and Computation. 475:128723

Témata: Markov renewal processes, semi-Markov processes, Signal theory (characterization, reconstruction, filtering, etc.), finite-time contractive bound, extended dissipative, sensor saturation, Numerical analysis or methods applied to Markov chains, asynchronous filter, Discrete event control/observation systems, dual-channel DoS attacks, Filtering in stochastic control theory

Popis souboru: application/xml

Přístupová URL adresa: https://zbmath.org/7879832
https://doi.org/10.1016/j.amc.2024.128723

Point Spread Function Estimation in X-Ray Imaging with Partially Collapsed Gibbs Sampling: Point spread function estimation in X-ray imaging with partially collapsed Gibbs sampling

Autoři: Kevin T. Joyce Johnathan M. Bardsley Aaron Luttman

Zdroj: SIAM Journal on Scientific Computing. 40:B766-B787

Témata: Biomedical imaging and signal processing, inverse problems, uncertainty quantification, Bayesian inference, Markov chain Monte Carlo methods, Monte Carlo methods, Numerical Analysis (math.NA), Computing methodologies for image processing, computational imaging, 01 natural sciences, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis, Image processing (compression, reconstruction, etc.) in information and communication theory, 65C05, 65C40, 68U10, 0101 mathematics

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/pdf/1709.09105
http://arxiv.org/abs/1709.09105

Convergence of metadynamics: Discussion of the adiabatic hypothesis: Convergence of metadynamics: discussion of the adiabatic hypothesis

Autoři: Jourdain, Benjamin Lelièvre, Tony Zitt, Pierre-André

Přispěvatelé: Jourdain, Benjamin Lelièvre, Tony Zitt, Pierre-André

Zdroj: The Annals of Applied Probability. 31

Témata: averaging, Probability (math.PR), FOS: Physical sciences, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], Computational Physics (physics.comp-ph), Dynamic and nonequilibrium phase transitions (general) in statistical mechanics, 01 natural sciences, metadynamics, Ray-Knight representation, exponential ergodicity, self-repelling diffusions, adaptive biasing dynamics, Computational methods in Markov chains, 0103 physical sciences, long time limit, FOS: Mathematics, adiabatic separation, Numerical analysis or methods applied to Markov chains, 0101 mathematics, Physics - Computational Physics, Computational methods for stochastic equations (aspects of stochastic analysis), Mathematics - Probability

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/pdf/1904.08667
http://arxiv.org/abs/1904.08667
https://zbmath.org/7420556
https://doi.org/10.1214/20-aap1652
https://hal.science/hal-02104961v1
https://doi.org/10.1214/20-aap1652
https://dialnet.unirioja.es/servlet/articulo?codigo=8127171
https://projecteuclid.org/journals/annals-of-applied-probability/volume-31/issue-5/Convergence-of-metadynamics-Discussion-of-the-adiabatic-hypothesis/10.1214/20-AAP1652.full
https://hal.archives-ouvertes.fr/hal-02104961v1

Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications: Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications

Autoři: Nikolaj T. Mücke Benjamin Sanderse Sander M. Bohté a další

Přispěvatelé: Nikolaj T. Mücke Benjamin Sanderse Sander M. Bohté a další

Zdroj: SSRN Electronic Journal.

Témata: Inverse problems, Generative adversarial networks, inverse problems, Bayesian inference, Monte Carlo methods, Numerical Analysis (math.NA), 01 natural sciences, Computational Mathematics, Markov chain Monte Carlo, Computational Theory and Mathematics, Modelling and Simulation, Computational methods in Markov chains, FOS: Mathematics, Numerical analysis or methods applied to Markov chains, Mathematics - Numerical Analysis, generative adversarial networks, 0101 mathematics, Computational methods for problems pertaining to statistics, Artificial neural networks and deep learning

Popis souboru: application/xml; application/pdf

Přístupová URL adresa: http://arxiv.org/pdf/2111.12408
http://arxiv.org/abs/2111.12408
https://hdl.handle.net/11245.1/abe9b85d-a447-4352-8326-99d9ef777671
https://doi.org/10.1016/j.camwa.2023.07.028
https://dare.uva.nl/personal/pure/en/publications/markov-chain-generative-adversarial-neural-networks-for-solving-bayesian-inverse-problems-in-physics-applications(abe9b85d-a447-4352-8326-99d9ef777671).html
https://research.rug.nl/en/publications/4ad10d3f-f2dc-411e-b5e2-90438c4328a7
https://doi.org/10.1016/j.camwa.2023.07.028
https://hdl.handle.net/11370/4ad10d3f-f2dc-411e-b5e2-90438c4328a7
https://dspace.library.uu.nl/handle/1874/433292

On parallelizable Markov chain Monte Carlo algorithms with waste-recycling

Autoři: Shihao Yang Espen Bernton Jun Liu a další

Zdroj: Statistics and Computing. 28:1073-1081

Témata: Markov chain Monte Carlo, Computational methods in Markov chains, Numerical analysis or methods applied to Markov chains, Monte Carlo methods, weighted samples, effective sample size, estimation efficiency, 0101 mathematics, Rao-Blackwellization, parallel computation, 01 natural sciences, 3. Good health, 12. Responsible consumption

Popis souboru: application/xml

Přístupová URL adresa: https://link.springer.com/article/10.1007/s11222-017-9780-4
https://dl.acm.org/doi/abs/10.1007/s11222-017-9780-4
https://link.springer.com/content/pdf/10.1007%2Fs11222-017-9780-4.pdf
https://doi.org/10.1007/s11222-017-9780-4
https://dblp.uni-trier.de/db/journals/sac/sac28.html#YangCBL18

Generating MCMC proposals by randomly rotating the regular simplex

Autoři: Andrew J. Holbrook

Zdroj: J Multivar Anal

Témata: Haar measure, FOS: Computer and information sciences, Other Statistics (stat.OT), Monte Carlo methods, 02 engineering and technology, parallel MCMC, Statistics - Computation, 01 natural sciences, Article, Markov chain Monte Carlo, Statistics - Other Statistics, 0202 electrical engineering, electronic engineering, information engineering, Numerical analysis or methods applied to Markov chains, 0101 mathematics, Computational methods for problems pertaining to statistics, Computation (stat.CO), orthogonal group

Popis souboru: application/xml

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37799825
http://arxiv.org/abs/2110.06445
https://zbmath.org/7636963
https://doi.org/10.1016/j.jmva.2022.105106

Replica Exchange Preconditioned Crank-Nicolson Langevin Dynamic MCMC Method with Multi-Variance Strategy for Bayesian Inverse Problems: A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems

Autoři: Na Ou Zecheng Zhang Guang Lin

Zdroj: Journal of Computational Physics. 510:113067

Témata: Bayesian inverse problem, preconditioned Crank-Nicolson scheme, Numerical solution to inverse problems in abstract spaces, Numerical analysis or methods applied to Markov chains, Langevin diffusion, replica exchange Monte Carlo

Popis souboru: application/xml

Přístupová URL adresa: https://zbmath.org/8021033
https://doi.org/10.1016/j.jcp.2024.113067

Block SOR for Kronecker structured representations

Autoři: Buchholz, P. Dayar, T.

Zdroj: Linear Algebra and Its Applications
Linear Algebra and its Applications

Témata: ddc:004, Computation theory, Iterative numerical methods for linear systems, Kronecker based numerical techniques, 0211 other engineering and technologies, hierarchical Markovian models, Gauss-Seidel method, 02 engineering and technology, Direct numerical methods for linear systems and matrix inversion, Matrix algebra, 01 natural sciences, Real Schur Factorization, Block Sor, Block SOR, column approximate minimum degree ordering algorithm, Computational methods in Markov chains, Discrete Mathematics and Combinatorics, block successive over-relaxation, Kronecker Based Numerical Techniques, 0101 mathematics, numerical experiments, Mathematical models, Numerical Analysis, Algebra and Number Theory, Markov chains, real Schur factorization, Markov processes, Approximation theory, COLAMD ordering, Computer simulation, Markov Chains, Markov chains, Kronecker based numerical techniques, block SOR, real Schur factorization, COLAMD ordering, Real Schur factorization, Markow-Ketten, Matrizenrechnung, Schurzerlegung, Schur-Faktorisierung, Algebra, Kronecker-Produkt, LU factorization, Numerical analysis or methods applied to Markov chains, Geometry and Topology, Colamd Ordering, Algorithms

Popis souboru: application/xml; application/pdf

Přístupová URL adresa: https://zbmath.org/2081258
https://doi.org/10.1016/j.laa.2003.12.017
https://www.sciencedirect.com/science/article/pii/S0024379503008917
https://tud.qucosa.de/id/qucosa%3A26304
https://core.ac.uk/display/52924242
http://yoksis.bilkent.edu.tr/pdf/files/10.1016-j.laa.2003.12.017.pdf
https://hdl.handle.net/11693/27455
https://hdl.handle.net/11693/13410
https://tud.qucosa.de/api/qucosa:26304/attachment/ATT-0/
https://tud.qucosa.de/id/qucosa:26304

Analysis of inhomogeneous Markov reward models

Autoři: HORVATH, Andras M. TELEK G. HORVÁTH

Zdroj: Linear Algebra and its Applications. 386:383-405

Témata: moments of reward measures, inhomogeneous continuous-time Markov chain, Numerical Analysis, Algebra and Number Theory, Ordinary and partial differential equations, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, numerical example, Computational methods in Markov chains, Inhomogeneous Markov reward models, Discrete Mathematics and Combinatorics, Numerical analysis or methods applied to Markov chains, ordinary and partial differential equations, Geometry and Topology, Moments of reward measures, 0101 mathematics, Continuous-time Markov processes on discrete state spaces, inhomogeneous Markov reward models

Popis souboru: application/xml; application/pdf

Přístupová URL adresa: https://zbmath.org/2081271
https://doi.org/10.1016/j.laa.2004.02.002
https://www.sciencedirect.com/science/article/pii/S0024379504000667
http://www.di.unito.it/~horvath/valutazione/publications/papers/TeHoHo04.pdf
https://core.ac.uk/display/20911109
https://www.sciencedirect.com/science/article/abs/pii/S0024379504000667
https://hdl.handle.net/2318/18374