Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Objectives To exploratorily examine whether parental rearing styles mediate the association between parental mental health and children’s anxiety tendencies and to explore whether these associations ...

Abstract: We are interested in solving linear systems arising from three applications: (1) kernel methods in machine learning, (2) discretization of boundary integral equations from mathematical ...

A hundred years ago this week, at the height of the quantum revolution, Austrian physicist Erwin Schrödinger submitted a manuscript for publication. Its centerpiece was an innocuous-looking equation ...

Harnessing the power of the sun holds the promise of providing future societies with energy abundance. To make this a reality, fusion researchers need to address many technological challenges. For ...

Quantum physics may sound abstract, but Ph.D. candidates Kirsten Kanneworff and David Dechant show that quantum research can also be very concrete. Together, they are investigating how quantum ...

Researchers at Santa Clara University have developed a comprehensive mathematical framework to rigorously analyze and predict ...

Abstract: Reachability analysis is a formal method to guarantee safety of dynamical systems under the influence of uncertainties. A substantial bottleneck of all reachability algorithms is the ...

Discover how Hyperbolic Absolute Risk Aversion models risk tolerance, influences investment choices, and simplifies financial ...

Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...

Mouse primary motor and somatosensory cortices contain detailed information about the many time-varying arm and paw joint angles during reaching and grasping, implying a 'low-level' role in ...

Dynamical low-rank approximation (DLRA) is an emerging tool for reducing computational costs and provide memory savings when solving high-dimensional problems. In this work, we propose and analyze a ...