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Abstract: Reversible logic circuits are one of the solutions to the problem of conventional microelectronic technology reaching its limits. Unfortunately, efficient reversible system design requires ...

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 ...

Functional beverages are exploding in 2026. Discover gut health drinks, electrolyte hydration, and adaptogen trends—and whether they actually work. This voice experience is generated by AI. Learn more ...

treehfd is a Python module to compute the Hoeffding functional decomposition of XGBoost models (Chen and Guestrin, 2016) with dependent input variables, using the TreeHFD algorithm. This decomposition ...

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 ...

This paper explores an alternative way for analyzing static Functional Connectivity (FC) in functional Magnetic Resonance Imaging (fMRI) data across multiple timescales using a class of adaptive ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

Leaf litter decomposition is a critical ecosystem-level process in many freshwater habitats. Although ponds are likely to derive a large proportion of their energy from riparian vegetation, ...

Abstract: This tutorial explores the class of non-parametric time series basis decomposition methods particularly suited for nonstationary time series known as Empirical Mode Decomposition (EMD). In ...