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20112021
most citedBayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment

144 citations · 383 across the 14 of their papers we have counts for

collaborators

15 papers

quant-ph2021

Relativistic Mechanics Theory for Electrons that Exhibits Spin, Zitterbewegung, Superposition and Produces Dirac's Wave Equation

James L. Beck

A neo-classical relativistic mechanics theory is presented where the spin of an electron is a natural part of its space-time path as a point particle. The fourth-order equation of…

stat.AP2019

Exploiting Convexification for Bayesian Optimal Sensor Placement by Maximization of Mutual Information

Pinaky Bhattacharyya, James L. Beck

Bayesian optimal sensor placement, in its full generality, seeks to maximize the mutual information between uncertain model parameters and the predicted data to be collected from t…

stat.CO2018★ 5 cited

Bayesian Updating and Uncertainty Quantification using Sequential Tempered MCMC with the Rank-One Modified Metropolis Algorithm

Thomas A. Catanach, James L. Beck

Bayesian methods are critical for quantifying the behaviors of systems. They capture our uncertainty about a system's behavior using probability distributions and update this under…

quant-ph2018★ 1 cited

Contrasting Implications of the Frequentist and Bayesian Interpretations of Probability when Applied to Quantum Mechanics Theory

James L. Beck

An examination is made of the differing implications from applying the two mainstream interpretations of probability, frequentist and Bayesian, to QM (quantum mechanics) theory for…

stat.AP2017★ 144 cited

Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment

Yong Huang, James L. Beck, Hui Li

The focus in this paper is Bayesian system identification based on noisy incomplete modal data where we can impose spatially-sparse stiffness changes when updating a structural mod…

stat.AP2016

Hierarchical Stochastic Model in Bayesian Inference: Theoretical Implications and Efficient Approximation

Stephen Wu, Panagiotis Angelikopoulos, James L. Beck +1

We classify two types of Hierarchical Bayesian Model found in the literature as Hierarchical Prior Model (HPM) and Hierarchical Stochastic Model (HSM). Then, we focus on studying t…