Abstract: Low-rank representations such as the Tucker decomposition underlie many frequentist methods for tensor analysis. Bayesian analogues, in contrast, have received less attention. Notably ...

The real-world data of power networks is often inaccessible due to privacy and security concerns, highlighting the need for tools to generate realistic synthetic network data. Existing methods ...

This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...

Version of Record: This is the final version of the article. This work proposes a new approach to analyse cell-count data from multiple brain regions. Collecting such data can be expensive and ...

The hierarchical flow for clock domain crossing (CDC) and reset domain crossing (RDC) is a methodology used in the verification of large, complex digital integrated circuits. It’s a divide-and-conquer ...

Over the past 60 years, scientists have largely succeeded in building a computer model of Earth to see what the future holds. One of the most ambitious projects humankind has ever undertaken has now ...

The hierarchical reasoning model (HRM) system is modeled on the way the human brain processes complex information, and it outperformed leading LLMs in a notoriously hard-to-beat benchmark. When you ...

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...

Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on ...