Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

The bvars package includes state-of-the-art Vector Autoregressive models with Minnesota priors and a flexible structure of the error term specification. The model ...

Abstract: In recent years, kernel machine learning algorithm (e.g. least square support vector machine, LSSVM) is a commonly method for time series prediction, as the main unit, the type of kernel ...

Valve’s Steam Machine desktop is currently in a state of involuntary limbo, driven by historically awful pricing and availability for memory and storage chips. AI data centers are absorbing much of ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Artificial intelligence is currently an active topic in both scientific research and commercial application as well as daily life. The linear operations of high-dimensional vectors are fundamental and ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...