Scientists have developed hundreds of techniques to measure the interactions between
pairs of processes in complex systems, but these computational methods—from …

Being able to capture the characteristics of a time series with a feature vector is a very
important task with a multitude of applications, such as classification, clustering or …

Background Real-time prediction is key to prevention and control of infections associated
with health-care settings. Contacts enable spread of many infections, yet most risk prediction …

The brain's complex distributed dynamics are typically quantified using a limited set of
manually selected statistical properties, leaving the possibility that alternative dynamical …

Dimension is a fundamental property of objects and the space in which they are embedded.
Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical …

A consolidated framework for quantifying interaction dynamics | Nature Computational Science
Skip to main content Thank you for visiting nature.com. You are using a browser version with …

Abstract Conventional Vector Autoregressive (VAR) modelling methods applied to high
dimensional neural time series data result in noisy solutions that are dense or have a large …

In recent years, there has been a surge in the prevalence of high-and multidimensional
temporal data across various scientific disciplines. These datasets are characterized by their …

针对现有图嵌入方法损失函数来源单一导致节点表示不能被充分优化的问题,
提出了基于同步联合优化的注意力图自编码器(attentionalgraphauto-encoderbasedonsynchronousjointoptimizati …

Biology, from the ancient Greek,“study of life”, is the most fascinating yet complex of all
sciences. Its understanding is paramount in solving many current problems we face in our …