Foundation models in molecular biology, leveraging their success in NLP and image generation, are revolutionizing the understanding of multi-level molecular correlations by training on vast datasets ...

A research team led by Prof. Li Hai from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has ...

Engaging community to co-design multilevel intervention to reduce lung cancer disparities in persistent poverty tracts through group model building and simulation.. If you have the appropriate ...

In elliptical multilevel models, the vector of the response variable is assumed to follow an elliptical multivariate distribution. A random vector follows an -dimensional elliptical distribution if ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

We review models for analyzing multivariate data of mixed (heterogeneous) domains such as binary, categorical, ordinal, counts, continuous, and/or skewed continuous, and methods for modeling various ...

However, existing methods mostly focus on optimizing model architectures without taking into account feature subspaces and model weights. In this work, we propose anomaly detection neuroevolution ...

Learn how multivariate methods can improve predictive modeling in data science and lead to more accurate insights and decisions.

Discover how multivariate analysis enhances predictive modeling accuracy and helps manage complex data in various industries.