The new reasoning AI, named the Hierarchical Reasoning Model (HRM), is inspired by the human brain's hierarchical and ...

Hierarchical models provide reliable statistical estimates for data sets from high-throughput experiments where measurements vastly outnumber experimental samples.

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...

Storage systems that are built around a hierarchical model will more easily accept XML data and will do so without having to perform relational and indexing gymnastics as they would with a ...

Louis M. Rocconi, Analyzing multilevel data: comparing findings from hierarchical linear modeling and ordinary least squares regression, Higher Education, Vol. 66, No. 4 (October 2013), pp. 439-461 ...

In this paper, we describe the hierarchical data model (HDM), which is a performance efficient alternative to the traditional flat CDC verification flow. The HDM is equivalent to an abstract CDC model ...

Hierarchical data model generation during IP verification: During IP-level CDC verification, a data model is generated along with CDC results. This HDM contains all the necessary information about the ...

A separate model is developed for each season to capture the unique spatial features prevalent in the precipitation field. This modeling framework offers a flexible approach to incorporate covariates ...

This work describes statistical modeling of detailed, microlevel automobile insurance records. We consider 1993-2001 data from a major insurance company in Singapore. By detailed microlevel records, ...