Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: Space-time adaptive processing (STAP) is a key technique for suppressing clutter. We develop a unified correlated sparse Bayesian learning (CSBL) framework to improve clutter suppression in ...

Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

A British-flagged luxury superyacht that sank off Sicily last year, killing UK tech magnate Mike Lynch and six others, completed its final trip to the Sicilian port of Termini Imerese Sunday, a day ...

Ten months after the luxury superyacht Bayesian sank off the coast of Sicily in a sudden storm, salvage crews managed to lift it 50 meters (164 feet) from the seabed on Friday afternoon, the company ...

In a world of uncertainty and shifting narratives, this post proposes a new model for investing: Bayesian edge investing. Unlike modern portfolio theory, which assumes equilibrium and perfect ...

Apple stealthily introduced Apple Sparse Image Format (ASIF), a new sparse disk image format for Apple Silicon, at WWDC; among other features, it might also help Macs remain the best PCs on which to ...

Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...