Zobrazeno 1 - 10
of 7 504
pro vyhledávání: '"Maskell, A"'
Sequential Monte Carlo Squared (SMC$^2$) is a Bayesian method which can infer the states and parameters of non-linear, non-Gaussian state-space models. The standard random-walk proposal in SMC$^2$ faces challenges, particularly with high-dimensional
Externí odkaz:
http://arxiv.org/abs/2407.17296
Autor:
Wu, Xuan, Wang, Di, Wen, Lijie, Xiao, Yubin, Wu, Chunguo, Wu, Yuesong, Yu, Chaoyu, Maskell, Douglas L., Zhou, You
Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing surveys did not cover the state-of-the-art (SOTA) NCO solvers emerged recen
Externí odkaz:
http://arxiv.org/abs/2406.00415
Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and Sequential Monte Carlo Squared (SMC$^2$) are two methods that use an u
Externí odkaz:
http://arxiv.org/abs/2311.12973
Autor:
Balasubramanian, P, Maskell, D L
Publikováno v:
Electronics, vol. 12, no. 18, Article #3819, 2023
Triple Modular Redundancy (TMR) has been traditionally used to ensure complete tolerance to a single fault or a faulty processing unit, where the processing unit may be a circuit or a system. However, TMR incurs more than 200% overhead in terms of ar
Externí odkaz:
http://arxiv.org/abs/2311.00328
This paper is concerned with sensor management for target search and track using the generalised optimal subpattern assignment (GOSPA) metric. Utilising the GOSPA metric to predict future system performance is computationally challenging, because of
Externí odkaz:
http://arxiv.org/abs/2308.07088
Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) because they can handle complex and uncertain data. Existing work on Bayesian DTs uses Markov Chain Monte Carlo (MCMC) with an
Externí odkaz:
http://arxiv.org/abs/2305.18774
This paper explores the effect of three-dimensional rotations on two-qubit Bell states and proposes a Bayesian method for the estimation of the parameters of the rotation. We use a particle filter to estimate the parameters of the rotation from a seq
Externí odkaz:
http://arxiv.org/abs/2304.05815
Autor:
Tim C. Passchier, Joshua B. R. White, Daniel P. Maskell, Matthew J. Byrne, Neil A. Ranson, Thomas A. Edwards, John N. Barr
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract We report the first cryoEM structure of the Hendra henipavirus nucleoprotein in complex with RNA, at 3.5 Å resolution, derived from single particle analysis of a double homotetradecameric RNA-bound N protein ring assembly exhibiting D14 sym
Externí odkaz:
https://doaj.org/article/83934cedf5894950befc177a6709b717
Autor:
Rachel Kwiatkowska, Anastasia Chatzilena, Jade King, Madeleine Clout, Serena McGuinness, Nick Maskell, Jennifer Oliver, Robert Challen, Matthew Hickman, Adam Finn, Catherine Hyams, Leon Danon, the AvonCAP Research Group
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in olde
Externí odkaz:
https://doaj.org/article/9891605e53ee4217898e23157a470ef4
Markov Chain Monte Carlo (MCMC) is a well-established family of algorithms primarily used in Bayesian statistics to sample from a target distribution when direct sampling is challenging. Existing work on Bayesian decision trees uses MCMC. Unfortunate
Externí odkaz:
http://arxiv.org/abs/2301.09090