As artificial intelligence (AI) continues to revolutionize industries, the health insurance sector is undergoing a pivotal ...

In this paper, we propose a novel path loss model based on multi-dimensional Gaussian ... a special structure consisting of a radial mean function and a local shadow fading term. In contrast to the ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

As data volumes surge across every industry and machine learning tools become ... to identify the best-performing model for a given dataset. It supports a variety of tasks, including classification, ...

Skoltech researchers have enlisted generative artificial intelligence to complete the missing data on the distances between ...

The authors introduce a machine learning model that brings structure and consistency to ... director of the Genomes2People Research Program at Mass General Brigham, and David Bick, MD, Ph.D ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet ...

This paper studies the relationship between export structure and growth performance. We design an export recommendation system using a collaborative filtering algorithm based on countries' revealed ...