Bayesian system identification based on hierarchical sparse Bayesian learning and Gibbs sampling with application to structural damage assessment
Sign Up to like & getrecommendations! Published in 2017 at "Computer Methods in Applied Mechanics and Engineering"
DOI: 10.1016/j.cma.2017.01.030
Abstract: Bayesian system identification has attracted substantial interest in recent years for inferring structural models based on measured dynamic response from a structural dynamical system. The focus in this paper is Bayesian system identification based on… read more here.
Keywords: system; bayesian system; system identification; damage ... See more keywords
ALiSa: Acrostic Linguistic Steganography Based on BERT and Gibbs Sampling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3152126
Abstract: In this letter, we propose a novel linguistic steganographic method that directly conceals a token-level secret message in a seemingly-natural steganographic text generated by the off-the-shelf BERT model equipped with Gibbs sampling. Compared with all… read more here.
Keywords: gibbs sampling; alisa acrostic; secret message; linguistic steganographic ... See more keywords
3D Placement for Multi-UAV Relaying: An Iterative Gibbs-Sampling and Block Coordinate Descent Optimization Approach
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2020.3043776
Abstract: In this paper, we consider an unmanned aerial vehicle (UAV) enabled relaying system where multiple UAVs are deployed as aerial relays to support simultaneous communications from a set of source nodes to their destination nodes… read more here.
Keywords: optimization; sampling block; method; iterative gibbs ... See more keywords
Student's $t$ VAR Modeling With Missing Data Via Stochastic EM and Gibbs Sampling
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2020.3033378
Abstract: The vector autoregressive (VAR) models provide a significant tool for multivariate time series analysis. Owing to the mathematical simplicity, existing works on VAR modeling are rigidly inclined towards the multivariate Gaussian distribution. However, heavy-tailed distributions… read more here.
Keywords: heavy tailed; student; missing data; gibbs sampling ... See more keywords
Gibbs Sampling in Inference of Copula Gaussian Graphical Model Adapted to Biological Networks
Sign Up to like & getrecommendations! Published in 2017 at "Acta Physica Polonica A"
DOI: 10.12693/aphyspola.132.1112
Abstract: Markov chain Monte Carlo methods (MCMC) are iterative algorithms that are used in many Bayesian simulation studies, where the inference cannot be easily obtained directly through the defined model. Reversible jump MCMC methods belong to… read more here.
Keywords: sampling inference; gaussian graphical; inference copula; model ... See more keywords
Bayesian Analysis Methods for Two-Level Diagnosis Classification Models
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Educational and Behavioral Statistics"
DOI: 10.3102/10769986231173594
Abstract: Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes… read more here.
Keywords: classification models; gibbs sampling; two level; level ... See more keywords