Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

we propose a novel path loss model based on multi-dimensional Gaussian process regression (GPR) that gives spatial consistency to channels in propagation environment by predicting local shadow fading ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

If you are looking for an introductory material on Julia, have a look on the book "Julia Quick Syntax Reference"(Apress,2019) or the online course "Scientific Programming and Machine Learning in Julia ...

Machine learning (ML) techniques and especially deep learning (DL) show potential in fast and accurate imaging. However, the high performance of purely data-driven approaches relies on constructing a ...

It is almost, but not quite, entirely unlike ASE, with some tools extending numpy/scipy. It has a set of powerful parsers and data types for storing calculation data.

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...