This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this ...
Current LLMs depend heavily on Chain-of-Thought prompting, an approach that often suffers from brittle task decomposition, immense training data demands and high latency. Inspired by the hierarchical ...
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 ...
February 11, 2021 - Insilico Medicine, a global leader in artificial intelligence (AI) for drug discovery and development, proposed a new molecular graph generative model called MolGrow at the 35th ...
Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available ...
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