Results 61 to 70 of about 151,127 (170)
Sequential Monte Carlo bandits
Foundations of Data ScienceThe software used for this study is publicly available at https://github.com/iurteaga ...
Urteaga, Iñigo, Wiggins, Chris H.
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A Sequential Monte Carlo Method for Motif Discovery [PDF]
IEEE Transactions on Signal Processing, 2008 Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Kuo-ching Liang +2 more
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Entropy, 2021 Heterogeneous reactions are chemical reactions that occur at the interfaces of multiple phases, and often show a nonlinear dynamical behavior due to the effect of the time-variant surface area with complex reaction mechanisms.
Masaki Ito +3 more
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Auto-Encoding Sequential Monte Carlo
, 2017 We build on auto-encoding sequential Monte Carlo (AESMC): a method for model and proposal learning based on maximizing the lower bound to the log marginal likelihood in a broad family of structured probabilistic models. Our approach relies on the efficiency of sequential Monte Carlo (SMC) for performing inference in structured probabilistic models and ...
Le, T +4 more
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Sequential Monte Carlo Sampling for DSGE Models [PDF]
SSRN Electronic Journal, 2012 We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples--an artificial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohe and Uribe ...
Edward P. Herbst, Frank Schorfheide
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New Journal of Physics, 2017 A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent ...
Christopher Granade, Nathan Wiebe
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Online sequential Monte Carlo smoother for partially observed diffusion processes
EURASIP Journal on Advances in Signal Processing, 2018 This paper introduces a new algorithm to approximate smoothed additive functionals of partially observed diffusion processes. This method relies on a new sequential Monte Carlo method which allows to compute such approximations online, i.e., as the ...
Pierre Gloaguen +2 more
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U.Porto Journal of Engineering, 2021 Reliability assessment of electrical distribution systems is an important criterion to determine system performance in terms of interruptions. Probabilistic assessment methods are usually used in reliability analysis to deal with uncertainties.
Manohar Potli, Chandrasekhar Reddy Atla
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Sequential change-point detection in a multinomial logistic regression model
Open Mathematics, 2020 Change-point detection in categorical time series has recently gained attention as statistical models incorporating change-points are common in practice, especially in the area of biomedicine.
Li Fuxiao, Chen Zhanshou, Xiao Yanting
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Application of Sequential Quasi-Monte Carlo to Autonomous Positioning
, 2015 Sequential Monte Carlo algorithms (also known as particle filters) are popular methods to approximate filtering (and related) distributions of state-space models.
Chopin, Nicolas, Gerber, Mathieu
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