Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Complex matrix algebra is of great importance to a wide variety of applications. One of the most important application areas is telecommunications. Matrix calculations are used in communications ...

Random walks serve as fundamental models in the study of stochastic processes, simulating phenomena ranging from molecular diffusion to queuing networks and financial systems. Their inherent ...

Most traditional high-performance computing applications focus on computations on very large matrices. Think seismic analysis, weather prediction, structural analysis. But today, with advances in deep ...