Results 31 to 40 of about 1,412,360 (277)
vSMC: Parallel Sequential Monte Carlo in C++
Journal of Statistical Software, 2015 Sequential Monte Carlo is a family of algorithms for sampling from a sequence of distributions. Some of these algorithms, such as particle filters, are widely used in physics and signal processing research. More recent developments have established their
Yan Zhou
doaj +1 more source
Bayesian optimization with informative parametric models via sequential Monte Carlo
Data-Centric Engineering, 2022 Bayesian optimization (BO) has been a successful approach to optimize expensive functions whose prior knowledge can be specified by means of a probabilistic model.
Rafael Oliveira +7 more
doaj +1 more source
Improved Sequential Stopping Rule for Monte Carlo Simulation [PDF]
, 2008 This letter presents an improved result on the negative-binomial Monte Carlo technique analyzed in a previous paper (L. Mendo and J. M. Hernando, ``A simple sequential stopping rule for Monte Carlo simulation,'' IEEE Trans. Commun., vol. 54, no.
Hernando Rábanos, José María +1 more
core +1 more source
Sequential Monte Carlo Bandits
CoRR, 2013 In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techniques. The framework naturally encompasses restless bandits, contextual bandits, and other bandit variants under a single inferential model. Despite the model's generality, we
Michael Cherkassky, Luke Bornn
openaire +2 more sources
A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter [PDF]
, 2011 Extended objects are characterised with multiple measurements originated from ifferent locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking in the presence of clutter. The problem
Gning, Amadou +3 more
core +4 more sources
Sequential Monte Carlo multiple testing [PDF]
Bioinformatics, 2011 AbstractMotivation: In molecular biology, as in many other scientific fields, the scale of analyses is ever increasing. Often, complex Monte Carlo simulation is required, sometimes within a large-scale multiple testing setting. The resulting computational costs may be prohibitively high.Results: We here present MCFDR, a simple, novel algorithm for ...
Geir Kjetil Sandve +2 more
openaire +3 more sources
SoftwareX, 2018 With proliferation of smart devices such as smart phones, it is common that an event is recorded by multiple individuals creating several audio and video perspectives. Such user generated content is mostly unorganized (not synchronized). In this work, we
Dogac Basaran +2 more
doaj +1 more source
Online Variational Sequential Monte Carlo
CoRR, 2023 Being the most classical generative model for serial data, state-space models (SSM) are fundamental in AI and statistical machine learning. In SSM, any form of parameter learning or latent state inference typically involves the computation of complex latent-state posteriors.
Alessandro Mastrototaro, Jimmy Olsson
openaire +3 more sources
On Sequential Bayesian Inference for Continual Learning
Entropy, 2023 Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks.
Samuel Kessler +4 more
doaj +1 more source
Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
Econometrics, 2016 Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain ...
Arnaud Dufays
doaj +1 more source