but they often fall short in achieving sufficient isotopic purity combined either with a site-selectivity or with a full deuteration process. Here, the authors report an approach to unlock the ...

Consequently, in this article, a novel decision-making method designed to meet the demands of multiple reactive tasks is proposed to serve autonomous driving sweepers. Smart nodes (smart sequence and ...

Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...

This process also provides an efficient framework for model development ... These parameters, being part of ensemble models built on decision trees, exhibited consistency across models. Subsequently, ...

Abstract: Gradient-boosting decision tree classifiers (GBDTs) are susceptible to adversarial perturbation attacks that change inputs slightly to cause misclassification. GBDTs are customarily used on ...

The Cleveland Browns own the No. 2 overall pick in the NFL Draft this year, and most are assuming that the Browns will play it safe and simply take a quarterback at that spot. After all, Cleveland ...

The danger of this approach is that it effectively provides no protection against disinformation: it is instead primarily geared at driving user engagement. ‘Evil thrives when good people do nothing’, ...

Western researchers have developed a novel technique using math to understand exactly how neural networks make decisions—a widely recognized but poorly understood process in the field of machine ...

"Our research shows that the material properties of the stones—such as suitability, quality, and durability—were likely crucial factors in the selection process by early hominins," explains ...