Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...

As part of "shift left" to incorporate security discussions earlier in the software development life cycle, organizations are beginning to look at threat modeling to identify security flaws in ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

Bernice Asantewaa Kyere on modeling that immediately caught my attention. The paper titled “A Critical Examination of Transformational Leadership in Implementing Flipped Classrooms for Mathematics ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Background and Goal: This study examined whether machine learning could predict the risk and contributing factors of no-shows and late cancellations in primary care practices. Study Approach: ...