Bayesian inverse modeling and source location of an unintended 131I release in Europe in the fall of 2011
In the fall of 2011, iodine-131 (131 I) was detected at several radionuclide monitoring
stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) …
stations in central Europe. After investigation, the International Atomic Energy Agency (IAEA) …
Bayesian non-negative matrix factorization with adaptive sparsity and smoothness prior
Non-negative matrix factorization (NMF) is generally an ill-posed problem which requires
further regularization. Regularization of NMF using the assumption of sparsity is common as …
further regularization. Regularization of NMF using the assumption of sparsity is common as …
[HTML][HTML] impulseest: A python package for non-parametric impulse response estimation with input–output data
This paper presents the impulseest Python package, used for estimating the impulse
response of a system relying solely on input and output data. This package can provide …
response of a system relying solely on input and output data. This package can provide …
Bayesian blind source separation with unknown prior covariance
The task of blind source separation (BSS) is to recover original signal sources which are
observed only via their superposition with unknown weights. Since we are interested in …
observed only via their superposition with unknown weights. Since we are interested in …
Semi-supervised Bayesian Source Separation of Scintigraphic Image Sequences
Many diagnostic methods using scintigraphic image sequence require decomposition of the
sequence into tissue images and their time-activity curves. Standard procedure for this task …
sequence into tissue images and their time-activity curves. Standard procedure for this task …
Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference
The choice of regularization for an ill-conditioned linear inverse problem has significant
impact on the resulting estimates. We consider a linear inverse model with on the solution in …
impact on the resulting estimates. We consider a linear inverse model with on the solution in …