In the suggested hierarchical model, an expression QTL (eQTL) model (which is essentially our missing data model) is part of the larger cQTL model and it represents a Bayesian model-based method ...

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

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

In this article, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data.

This model fits empirical data, and explains why equilibrium theory predicts behavior well in some games and poorly in others. An average of 1.5 steps fits data from many games. The Quarterly Journal ...

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 ...

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 ...

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 ...