Around the world, people plan to plant more than 1 trillion trees this decade in an ambitious effort to slow climate change ...

Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...

The controversial weed killer Roundup is being sprayed in record amounts in California’s forests. We go inside the secret ...

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...

Trained on historical consumption data spanning a decade, the model demonstrated strong predictive performance. It achieved a training error of 0.182 and a forecasting accuracy of 95.2 percent, ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

The move deepened the idea that a Vietnam-era law, which says congressionally unauthorized deployments into “hostilities” must end after 60 days, does not apply to airstrike campaigns. By Charlie ...

Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

ABSTRACT: Credit risk assessment plays an important role in financial services by estimating the chance of a borrower defaulting. Recently, although the Large Language Models (LLMs) have demonstrated ...