Abstract: This article presents methods for correct decomposition for high performance computations related to large sets of graphs. These computations contain large number of calls of sequential, ...

A strong core is not only a total flex—literally—it’s key for building total-body strength that carries over into everyday movement. And building one requires functional core training. Functional ...

Adaptive decomposition techniques have emerged as a pivotal class of methods in functional analysis, unifying approximation theory, operator theory and signal processing under a common framework. At ...

Under the hood, glex relies on fast algorithms to compute all required partial dependence functions exactly. For a detailed description of the methodology, see: See the accompanying paper for more ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jctc.5c01234.

Tensor decomposition is a fundamental tool for analyzing multi-dimensional data by learning low-rank factors to represent high-order interactions. While recent works on temporal tensor decomposition ...

Established morpho-functional chest magnetic resonance imaging (MRI) detects abnormalities in lung morphology and perfusion in people with cystic fibrosis (pwCF) using a dedicated scoring system.

Java-based coffee machine simulator that serves espresso, cappuccino, and latte while managing supplies, handling user input, and collecting money. Learn OOP fundamentals, classes, methods, loops, and ...

Abstract: FPGA technology mapping is an extensively studied problem. There is functional decomposition as well as graph covering-based approaches. For efficiency consideration, most existing ...

Many complex data analysis problems within and beyond the scientific domain involve discovering graphical structures and functional relationships within data. Nonlinear variance decomposition with ...